can all problems be solved using the scientific method

What is the Scientific Method: How does it work and why is it important?

The scientific method is a systematic process involving steps like defining questions, forming hypotheses, conducting experiments, and analyzing data. It minimizes biases and enables replicable research, leading to groundbreaking discoveries like Einstein's theory of relativity, penicillin, and the structure of DNA. This ongoing approach promotes reason, evidence, and the pursuit of truth in science.

Updated on November 18, 2023

Beginning in elementary school, we are exposed to the scientific method and taught how to put it into practice. As a tool for learning, it prepares children to think logically and use reasoning when seeking answers to questions.

Rather than jumping to conclusions, the scientific method gives us a recipe for exploring the world through observation and trial and error. We use it regularly, sometimes knowingly in academics or research, and sometimes subconsciously in our daily lives.

In this article we will refresh our memories on the particulars of the scientific method, discussing where it comes from, which elements comprise it, and how it is put into practice. Then, we will consider the importance of the scientific method, who uses it and under what circumstances.

What is the scientific method?

The scientific method is a dynamic process that involves objectively investigating questions through observation and experimentation . Applicable to all scientific disciplines, this systematic approach to answering questions is more accurately described as a flexible set of principles than as a fixed series of steps.

The following representations of the scientific method illustrate how it can be both condensed into broad categories and also expanded to reveal more and more details of the process. These graphics capture the adaptability that makes this concept universally valuable as it is relevant and accessible not only across age groups and educational levels but also within various contexts.

Steps in the scientific method

While the scientific method is versatile in form and function, it encompasses a collection of principles that create a logical progression to the process of problem solving:

• Define a question : Constructing a clear and precise problem statement that identifies the main question or goal of the investigation is the first step. The wording must lend itself to experimentation by posing a question that is both testable and measurable.
• Gather information and resources : Researching the topic in question to find out what is already known and what types of related questions others are asking is the next step in this process. This background information is vital to gaining a full understanding of the subject and in determining the best design for experiments. 
• Form a hypothesis : Composing a concise statement that identifies specific variables and potential results, which can then be tested, is a crucial step that must be completed before any experimentation. An imperfection in the composition of a hypothesis can result in weaknesses to the entire design of an experiment.
• Perform the experiments : Testing the hypothesis by performing replicable experiments and collecting resultant data is another fundamental step of the scientific method. By controlling some elements of an experiment while purposely manipulating others, cause and effect relationships are established.
• Analyze the data : Interpreting the experimental process and results by recognizing trends in the data is a necessary step for comprehending its meaning and supporting the conclusions. Drawing inferences through this systematic process lends substantive evidence for either supporting or rejecting the hypothesis.
• Report the results : Sharing the outcomes of an experiment, through an essay, presentation, graphic, or journal article, is often regarded as a final step in this process. Detailing the project's design, methods, and results not only promotes transparency and replicability but also adds to the body of knowledge for future research.
• Retest the hypothesis : Repeating experiments to see if a hypothesis holds up in all cases is a step that is manifested through varying scenarios. Sometimes a researcher immediately checks their own work or replicates it at a future time, or another researcher will repeat the experiments to further test the hypothesis.

Where did the scientific method come from?

Oftentimes, ancient peoples attempted to answer questions about the unknown by:

• Making simple observations
• Discussing the possibilities with others deemed worthy of a debate
• Drawing conclusions based on dominant opinions and preexisting beliefs

For example, take Greek and Roman mythology. Myths were used to explain everything from the seasons and stars to the sun and death itself.

However, as societies began to grow through advancements in agriculture and language, ancient civilizations like Egypt and Babylonia shifted to a more rational analysis for understanding the natural world. They increasingly employed empirical methods of observation and experimentation that would one day evolve into the scientific method . 

In the 4th century, Aristotle, considered the Father of Science by many, suggested these elements , which closely resemble the contemporary scientific method, as part of his approach for conducting science:

• Study what others have written about the subject.
• Look for the general consensus about the subject.
• Perform a systematic study of everything even partially related to the topic.

By continuing to emphasize systematic observation and controlled experiments, scholars such as Al-Kindi and Ibn al-Haytham helped expand this concept throughout the Islamic Golden Age . 

In his 1620 treatise, Novum Organum , Sir Francis Bacon codified the scientific method, arguing not only that hypotheses must be tested through experiments but also that the results must be replicated to establish a truth. Coming at the height of the Scientific Revolution, this text made the scientific method accessible to European thinkers like Galileo and Isaac Newton who then put the method into practice.

As science modernized in the 19th century, the scientific method became more formalized, leading to significant breakthroughs in fields such as evolution and germ theory. Today, it continues to evolve, underpinning scientific progress in diverse areas like quantum mechanics, genetics, and artificial intelligence.

Why is the scientific method important?

The history of the scientific method illustrates how the concept developed out of a need to find objective answers to scientific questions by overcoming biases based on fear, religion, power, and cultural norms. This still holds true today.

By implementing this standardized approach to conducting experiments, the impacts of researchers’ personal opinions and preconceived notions are minimized. The organized manner of the scientific method prevents these and other mistakes while promoting the replicability and transparency necessary for solid scientific research.

The importance of the scientific method is best observed through its successes, for example: 

• “ Albert Einstein stands out among modern physicists as the scientist who not only formulated a theory of revolutionary significance but also had the genius to reflect in a conscious and technical way on the scientific method he was using.” Devising a hypothesis based on the prevailing understanding of Newtonian physics eventually led Einstein to devise the theory of general relativity .
• Howard Florey “Perhaps the most useful lesson which has come out of the work on penicillin has been the demonstration that success in this field depends on the development and coordinated use of technical methods.” After discovering a mold that prevented the growth of Staphylococcus bacteria, Dr. Alexander Flemimg designed experiments to identify and reproduce it in the lab, thus leading to the development of penicillin .
• James D. Watson “Every time you understand something, religion becomes less likely. Only with the discovery of the double helix and the ensuing genetic revolution have we had grounds for thinking that the powers held traditionally to be the exclusive property of the gods might one day be ours. . . .” By using wire models to conceive a structure for DNA, Watson and Crick crafted a hypothesis for testing combinations of amino acids, X-ray diffraction images, and the current research in atomic physics, resulting in the discovery of DNA’s double helix structure .

Final thoughts

As the cases exemplify, the scientific method is never truly completed, but rather started and restarted. It gave these researchers a structured process that was easily replicated, modified, and built upon. 

While the scientific method may “end” in one context, it never literally ends. When a hypothesis, design, methods, and experiments are revisited, the scientific method simply picks up where it left off. Each time a researcher builds upon previous knowledge, the scientific method is restored with the pieces of past efforts.

By guiding researchers towards objective results based on transparency and reproducibility, the scientific method acts as a defense against bias, superstition, and preconceived notions. As we embrace the scientific method's enduring principles, we ensure that our quest for knowledge remains firmly rooted in reason, evidence, and the pursuit of truth.

The AJE Team

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A Guide to Using the Scientific Method in Everyday Life

The  scientific method —the process used by scientists to understand the natural world—has the merit of investigating natural phenomena in a rigorous manner. Working from hypotheses, scientists draw conclusions based on empirical data. These data are validated on large-scale numbers and take into consideration the intrinsic variability of the real world. For people unfamiliar with its intrinsic jargon and formalities, science may seem esoteric. And this is a huge problem: science invites criticism because it is not easily understood. So why is it important, then, that every person understand how science is done?

Because the scientific method is, first of all, a matter of logical reasoning and only afterwards, a procedure to be applied in a laboratory.

Individuals without training in logical reasoning are more easily victims of distorted perspectives about themselves and the world. An example is represented by the so-called “ cognitive biases ”—systematic mistakes that individuals make when they try to think rationally, and which lead to erroneous or inaccurate conclusions. People can easily  overestimate the relevance  of their own behaviors and choices. They can  lack the ability to self-estimate the quality of their performances and thoughts . Unconsciously, they could even end up selecting only the arguments  that support their hypothesis or beliefs . This is why the scientific framework should be conceived not only as a mechanism for understanding the natural world, but also as a framework for engaging in logical reasoning and discussion.

A brief history of the scientific method

The scientific method has its roots in the sixteenth and seventeenth centuries. Philosophers Francis Bacon and René Descartes are often credited with formalizing the scientific method because they contrasted the idea that research should be guided by metaphysical pre-conceived concepts of the nature of reality—a position that, at the time,  was highly supported by their colleagues . In essence, Bacon thought that  inductive reasoning based on empirical observation was critical to the formulation of hypotheses  and the  generation of new understanding : general or universal principles describing how nature works are derived only from observations of recurring phenomena and data recorded from them. The inductive method was used, for example, by the scientist Rudolf Virchow to formulate the third principle of the notorious  cell theory , according to which every cell derives from a pre-existing one. The rationale behind this conclusion is that because all observations of cell behavior show that cells are only derived from other cells, this assertion must be always true. 

Inductive reasoning, however, is not immune to mistakes and limitations. Referring back to cell theory, there may be rare occasions in which a cell does not arise from a pre-existing one, even though we haven’t observed it yet—our observations on cell behavior, although numerous, can still benefit from additional observations to either refute or support the conclusion that all cells arise from pre-existing ones. And this is where limited observations can lead to erroneous conclusions reasoned inductively. In another example, if one never has seen a swan that is not white, they might conclude that all swans are white, even when we know that black swans do exist, however rare they may be.  

The universally accepted scientific method, as it is used in science laboratories today, is grounded in  hypothetico-deductive reasoning . Research progresses via iterative empirical testing of formulated, testable hypotheses (formulated through inductive reasoning). A testable hypothesis is one that can be rejected (falsified) by empirical observations, a concept known as the  principle of falsification . Initially, ideas and conjectures are formulated. Experiments are then performed to test them. If the body of evidence fails to reject the hypothesis, the hypothesis stands. It stands however until and unless another (even singular) empirical observation falsifies it. However, just as with inductive reasoning, hypothetico-deductive reasoning is not immune to pitfalls—assumptions built into hypotheses can be shown to be false, thereby nullifying previously unrejected hypotheses. The bottom line is that science does not work to prove anything about the natural world. Instead, it builds hypotheses that explain the natural world and then attempts to find the hole in the reasoning (i.e., it works to disprove things about the natural world).

How do scientists test hypotheses?

Controlled experiments

The word “experiment” can be misleading because it implies a lack of control over the process. Therefore, it is important to understand that science uses controlled experiments in order to test hypotheses and contribute new knowledge. So what exactly is a controlled experiment, then? 

Let us take a practical example. Our starting hypothesis is the following: we have a novel drug that we think inhibits the division of cells, meaning that it prevents one cell from dividing into two cells (recall the description of cell theory above). To test this hypothesis, we could treat some cells with the drug on a plate that contains nutrients and fuel required for their survival and division (a standard cell biology assay). If the drug works as expected, the cells should stop dividing. This type of drug might be useful, for example, in treating cancers because slowing or stopping the division of cells would result in the slowing or stopping of tumor growth.

Although this experiment is relatively easy to do, the mere process of doing science means that several experimental variables (like temperature of the cells or drug, dosage, and so on) could play a major role in the experiment. This could result in a failed experiment when the drug actually does work, or it could give the appearance that the drug is working when it is not. Given that these variables cannot be eliminated, scientists always run control experiments in parallel to the real ones, so that the effects of these other variables can be determined.  Control experiments  are designed so that all variables, with the exception of the one under investigation, are kept constant. In simple terms, the conditions must be identical between the control and the actual experiment.     

Coming back to our example, when a drug is administered it is not pure. Often, it is dissolved in a solvent like water or oil. Therefore, the perfect control to the actual experiment would be to administer pure solvent (without the added drug) at the same time and with the same tools, where all other experimental variables (like temperature, as mentioned above) are the same between the two (Figure 1). Any difference in effect on cell division in the actual experiment here can be attributed to an effect of the drug because the effects of the solvent were controlled.

In order to provide evidence of the quality of a single, specific experiment, it needs to be performed multiple times in the same experimental conditions. We call these multiple experiments “replicates” of the experiment (Figure 2). The more replicates of the same experiment, the more confident the scientist can be about the conclusions of that experiment under the given conditions. However, multiple replicates under the same experimental conditions  are of no help  when scientists aim at acquiring more empirical evidence to support their hypothesis. Instead, they need  independent experiments  (Figure 3), in their own lab and in other labs across the world, to validate their results. 

Often times, especially when a given experiment has been repeated and its outcome is not fully clear, it is better  to find alternative experimental assays  to test the hypothesis. 

Applying the scientific approach to everyday life

So, what can we take from the scientific approach to apply to our everyday lives?

A few weeks ago, I had an agitated conversation with a bunch of friends concerning the following question: What is the definition of intelligence?

Defining “intelligence” is not easy. At the beginning of the conversation, everybody had a different, “personal” conception of intelligence in mind, which – tacitly – implied that the conversation could have taken several different directions. We realized rather soon that someone thought that an intelligent person is whoever is able to adapt faster to new situations; someone else thought that an intelligent person is whoever is able to deal with other people and empathize with them. Personally, I thought that an intelligent person is whoever displays high cognitive skills, especially in abstract reasoning. 

The scientific method has the merit of providing a reference system, with precise protocols and rules to follow. Remember: experiments must be reproducible, which means that an independent scientists in a different laboratory, when provided with the same equipment and protocols, should get comparable results.  Fruitful conversations as well need precise language, a kind of reference vocabulary everybody should agree upon, in order to discuss about the same “content”. This is something we often forget, something that was somehow missing at the opening of the aforementioned conversation: even among friends, we should always agree on premises, and define them in a rigorous manner, so that they are the same for everybody. When speaking about “intelligence”, we must all make sure we understand meaning and context of the vocabulary adopted in the debate (Figure 4, point 1).  This is the first step of “controlling” a conversation.

There is another downside that a discussion well-grounded in a scientific framework would avoid. The mistake is not structuring the debate so that all its elements, except for the one under investigation, are kept constant (Figure 4, point 2). This is particularly true when people aim at making comparisons between groups to support their claim. For example, they may try to define what intelligence is by comparing the  achievements in life of different individuals: “Stephen Hawking is a brilliant example of intelligence because of his great contribution to the physics of black holes”. This statement does not help to define what intelligence is, simply because it compares Stephen Hawking, a famous and exceptional physicist, to any other person, who statistically speaking, knows nothing about physics. Hawking first went to the University of Oxford, then he moved to the University of Cambridge. He was in contact with the most influential physicists on Earth. Other people were not. All of this, of course, does not disprove Hawking’s intelligence; but from a logical and methodological point of view, given the multitude of variables included in this comparison, it cannot prove it. Thus, the sentence “Stephen Hawking is a brilliant example of intelligence because of his great contribution to the physics of black holes” is not a valid argument to describe what intelligence is. If we really intend to approximate a definition of intelligence, Steven Hawking should be compared to other physicists, even better if they were Hawking’s classmates at the time of college, and colleagues afterwards during years of academic research. 

In simple terms, as scientists do in the lab, while debating we should try to compare groups of elements that display identical, or highly similar, features. As previously mentioned, all variables – except for the one under investigation – must be kept constant.

This insightful piece  presents a detailed analysis of how and why science can help to develop critical thinking.

In a nutshell

Here is how to approach a daily conversation in a rigorous, scientific manner:

• First discuss about the reference vocabulary, then discuss about the content of the discussion.  Think about a researcher who is writing down an experimental protocol that will be used by thousands of other scientists in varying continents. If the protocol is rigorously written, all scientists using it should get comparable experimental outcomes. In science this means reproducible knowledge, in daily life this means fruitful conversations in which individuals are on the same page. 
• Adopt “controlled” arguments to support your claims.  When making comparisons between groups, visualize two blank scenarios. As you start to add details to both of them, you have two options. If your aim is to hide a specific detail, the better is to design the two scenarios in a completely different manner—it is to increase the variables. But if your intention is to help the observer to isolate a specific detail, the better is to design identical scenarios, with the exception of the intended detail—it is therefore to keep most of the variables constant. This is precisely how scientists ideate adequate experiments to isolate new pieces of knowledge, and how individuals should orchestrate their thoughts in order to test them and facilitate their comprehension to others.   

Not only the scientific method should offer individuals an elitist way to investigate reality, but also an accessible tool to properly reason and discuss about it.

Edited by Jason Organ, PhD, Indiana University School of Medicine.

Simone is a molecular biologist on the verge of obtaining a doctoral title at the University of Ulm, Germany. He is Vice-Director at Culturico (https://culturico.com/), where his writings span from Literature to Sociology, from Philosophy to Science. His writings recently appeared in Psychology Today, openDemocracy, Splice Today, Merion West, Uncommon Ground and The Society Pages. Follow Simone on Twitter: @simredaelli

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This has to be the best article I have ever read on Scientific Thinking. I am presently writing a treatise on how Scientific thinking can be adopted to entreat all situations.And how, a 4 year old child can be taught to adopt Scientific thinking, so that, the child can look at situations that bothers her and she could try to think about that situation by formulating the right questions. She may not have the tools to find right answers? But, forming questions by using right technique ? May just make her find a way to put her mind to rest even at that level. That is why, 4 year olds are often “eerily: (!)intelligent, I have iften been intimidated and plain embarrassed to see an intelligent and well spoken 4 year old deal with celibrity ! Of course, there are a lot of variables that have to be kept in mind in order to train children in such controlled thinking environment, as the screenplay of little Sheldon shows. Thanking the author with all my heart – #ershadspeak #wearescience #weareallscientists Ershad Khandker

Simone, thank you for this article. I have the idea that I want to apply what I learned in Biology to everyday life. You addressed this issue, and have given some basic steps in using the scientific method.

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Sat / act prep online guides and tips, the 6 scientific method steps and how to use them.

General Education

When you’re faced with a scientific problem, solving it can seem like an impossible prospect. There are so many possible explanations for everything we see and experience—how can you possibly make sense of them all? Science has a simple answer: the scientific method.

The scientific method is a method of asking and answering questions about the world. These guiding principles give scientists a model to work through when trying to understand the world, but where did that model come from, and how does it work?

In this article, we’ll define the scientific method, discuss its long history, and cover each of the scientific method steps in detail.

What Is the Scientific Method?

At its most basic, the scientific method is a procedure for conducting scientific experiments. It’s a set model that scientists in a variety of fields can follow, going from initial observation to conclusion in a loose but concrete format.

The number of steps varies, but the process begins with an observation, progresses through an experiment, and concludes with analysis and sharing data. One of the most important pieces to the scientific method is skepticism —the goal is to find truth, not to confirm a particular thought. That requires reevaluation and repeated experimentation, as well as examining your thinking through rigorous study.

There are in fact multiple scientific methods, as the basic structure can be easily modified.  The one we typically learn about in school is the basic method, based in logic and problem solving, typically used in “hard” science fields like biology, chemistry, and physics. It may vary in other fields, such as psychology, but the basic premise of making observations, testing, and continuing to improve a theory from the results remain the same.

The History of the Scientific Method

The scientific method as we know it today is based on thousands of years of scientific study. Its development goes all the way back to ancient Mesopotamia, Greece, and India.

The Ancient World

In ancient Greece, Aristotle devised an inductive-deductive process , which weighs broad generalizations from data against conclusions reached by narrowing down possibilities from a general statement. However, he favored deductive reasoning, as it identifies causes, which he saw as more important.

Aristotle wrote a great deal about logic and many of his ideas about reasoning echo those found in the modern scientific method, such as ignoring circular evidence and limiting the number of middle terms between the beginning of an experiment and the end. Though his model isn’t the one that we use today, the reliance on logic and thorough testing are still key parts of science today.

The Middle Ages

The next big step toward the development of the modern scientific method came in the Middle Ages, particularly in the Islamic world. Ibn al-Haytham, a physicist from what we now know as Iraq, developed a method of testing, observing, and deducing for his research on vision. al-Haytham was critical of Aristotle’s lack of inductive reasoning, which played an important role in his own research.

Other scientists, including Abū Rayhān al-Bīrūnī, Ibn Sina, and Robert Grosseteste also developed models of scientific reasoning to test their own theories. Though they frequently disagreed with one another and Aristotle, those disagreements and refinements of their methods led to the scientific method we have today.

Following those major developments, particularly Grosseteste’s work, Roger Bacon developed his own cycle of observation (seeing that something occurs), hypothesis (making a guess about why that thing occurs), experimentation (testing that the thing occurs), and verification (an outside person ensuring that the result of the experiment is consistent).

After joining the Franciscan Order, Bacon was granted a special commission to write about science; typically, Friars were not allowed to write books or pamphlets. With this commission, Bacon outlined important tenets of the scientific method, including causes of error, methods of knowledge, and the differences between speculative and experimental science. He also used his own principles to investigate the causes of a rainbow, demonstrating the method’s effectiveness.

Scientific Revolution

Throughout the Renaissance, more great thinkers became involved in devising a thorough, rigorous method of scientific study. Francis Bacon brought inductive reasoning further into the method, whereas Descartes argued that the laws of the universe meant that deductive reasoning was sufficient. Galileo’s research was also inductive reasoning-heavy, as he believed that researchers could not account for every possible variable; therefore, repetition was necessary to eliminate faulty hypotheses and experiments.

All of this led to the birth of the Scientific Revolution , which took place during the sixteenth and seventeenth centuries. In 1660, a group of philosophers and physicians joined together to work on scientific advancement. After approval from England’s crown , the group became known as the Royal Society, which helped create a thriving scientific community and an early academic journal to help introduce rigorous study and peer review.

Previous generations of scientists had touched on the importance of induction and deduction, but Sir Isaac Newton proposed that both were equally important. This contribution helped establish the importance of multiple kinds of reasoning, leading to more rigorous study.

As science began to splinter into separate areas of study, it became necessary to define different methods for different fields. Karl Popper was a leader in this area—he established that science could be subject to error, sometimes intentionally. This was particularly tricky for “soft” sciences like psychology and social sciences, which require different methods. Popper’s theories furthered the divide between sciences like psychology and “hard” sciences like chemistry or physics.

Paul Feyerabend argued that Popper’s methods were too restrictive for certain fields, and followed a less restrictive method hinged on “anything goes,” as great scientists had made discoveries without the Scientific Method. Feyerabend suggested that throughout history scientists had adapted their methods as necessary, and that sometimes it would be necessary to break the rules. This approach suited social and behavioral scientists particularly well, leading to a more diverse range of models for scientists in multiple fields to use.

The Scientific Method Steps

Though different fields may have variations on the model, the basic scientific method is as follows:

#1: Make Observations 

Notice something, such as the air temperature during the winter, what happens when ice cream melts, or how your plants behave when you forget to water them.

#2: Ask a Question

Turn your observation into a question. Why is the temperature lower during the winter? Why does my ice cream melt? Why does my toast always fall butter-side down?

This step can also include doing some research. You may be able to find answers to these questions already, but you can still test them!

#3: Make a Hypothesis

A hypothesis is an educated guess of the answer to your question. Why does your toast always fall butter-side down? Maybe it’s because the butter makes that side of the bread heavier.

A good hypothesis leads to a prediction that you can test, phrased as an if/then statement. In this case, we can pick something like, “If toast is buttered, then it will hit the ground butter-first.”

#4: Experiment

Your experiment is designed to test whether your predication about what will happen is true. A good experiment will test one variable at a time —for example, we’re trying to test whether butter weighs down one side of toast, making it more likely to hit the ground first.

The unbuttered toast is our control variable. If we determine the chance that a slice of unbuttered toast, marked with a dot, will hit the ground on a particular side, we can compare those results to our buttered toast to see if there’s a correlation between the presence of butter and which way the toast falls.

If we decided not to toast the bread, that would be introducing a new question—whether or not toasting the bread has any impact on how it falls. Since that’s not part of our test, we’ll stick with determining whether the presence of butter has any impact on which side hits the ground first.

#5: Analyze Data

After our experiment, we discover that both buttered toast and unbuttered toast have a 50/50 chance of hitting the ground on the buttered or marked side when dropped from a consistent height, straight down. It looks like our hypothesis was incorrect—it’s not the butter that makes the toast hit the ground in a particular way, so it must be something else.

Since we didn’t get the desired result, it’s back to the drawing board. Our hypothesis wasn’t correct, so we’ll need to start fresh. Now that you think about it, your toast seems to hit the ground butter-first when it slides off your plate, not when you drop it from a consistent height. That can be the basis for your new experiment.

#6: Communicate Your Results

Good science needs verification. Your experiment should be replicable by other people, so you can put together a report about how you ran your experiment to see if other peoples’ findings are consistent with yours.

This may be useful for class or a science fair. Professional scientists may publish their findings in scientific journals, where other scientists can read and attempt their own versions of the same experiments. Being part of a scientific community helps your experiments be stronger because other people can see if there are flaws in your approach—such as if you tested with different kinds of bread, or sometimes used peanut butter instead of butter—that can lead you closer to a good answer.

A Scientific Method Example: Falling Toast

We’ve run through a quick recap of the scientific method steps, but let’s look a little deeper by trying again to figure out why toast so often falls butter side down.

#1: Make Observations

At the end of our last experiment, where we learned that butter doesn’t actually make toast more likely to hit the ground on that side, we remembered that the times when our toast hits the ground butter side first are usually when it’s falling off a plate.

The easiest question we can ask is, “Why is that?”

We can actually search this online and find a pretty detailed answer as to why this is true. But we’re budding scientists—we want to see it in action and verify it for ourselves! After all, good science should be replicable, and we have all the tools we need to test out what’s really going on.

Why do we think that buttered toast hits the ground butter-first? We know it’s not because it’s heavier, so we can strike that out. Maybe it’s because of the shape of our plate?

That’s something we can test. We’ll phrase our hypothesis as, “If my toast slides off my plate, then it will fall butter-side down.”

Just seeing that toast falls off a plate butter-side down isn’t enough for us. We want to know why, so we’re going to take things a step further—we’ll set up a slow-motion camera to capture what happens as the toast slides off the plate.

We’ll run the test ten times, each time tilting the same plate until the toast slides off. We’ll make note of each time the butter side lands first and see what’s happening on the video so we can see what’s going on.

When we review the footage, we’ll likely notice that the bread starts to flip when it slides off the edge, changing how it falls in a way that didn’t happen when we dropped it ourselves.

That answers our question, but it’s not the complete picture —how do other plates affect how often toast hits the ground butter-first? What if the toast is already butter-side down when it falls? These are things we can test in further experiments with new hypotheses!

Now that we have results, we can share them with others who can verify our results. As mentioned above, being part of the scientific community can lead to better results. If your results were wildly different from the established thinking about buttered toast, that might be cause for reevaluation. If they’re the same, they might lead others to make new discoveries about buttered toast. At the very least, you have a cool experiment you can share with your friends!

Key Scientific Method Tips

Though science can be complex, the benefit of the scientific method is that it gives you an easy-to-follow means of thinking about why and how things happen. To use it effectively, keep these things in mind!

Don’t Worry About Proving Your Hypothesis

One of the important things to remember about the scientific method is that it’s not necessarily meant to prove your hypothesis right. It’s great if you do manage to guess the reason for something right the first time, but the ultimate goal of an experiment is to find the true reason for your observation to occur, not to prove your hypothesis right.

Good science sometimes means that you’re wrong. That’s not a bad thing—a well-designed experiment with an unanticipated result can be just as revealing, if not more, than an experiment that confirms your hypothesis.

Be Prepared to Try Again

If the data from your experiment doesn’t match your hypothesis, that’s not a bad thing. You’ve eliminated one possible explanation, which brings you one step closer to discovering the truth.

The scientific method isn’t something you’re meant to do exactly once to prove a point. It’s meant to be repeated and adapted to bring you closer to a solution. Even if you can demonstrate truth in your hypothesis, a good scientist will run an experiment again to be sure that the results are replicable. You can even tweak a successful hypothesis to test another factor, such as if we redid our buttered toast experiment to find out whether different kinds of plates affect whether or not the toast falls butter-first. The more we test our hypothesis, the stronger it becomes!

What’s Next?

Want to learn more about the scientific method? These important high school science classes will no doubt cover it in a variety of different contexts.

Test your ability to follow the scientific method using these at-home science experiments for kids !

Need some proof that science is fun? Try making slime

Melissa Brinks graduated from the University of Washington in 2014 with a Bachelor's in English with a creative writing emphasis. She has spent several years tutoring K-12 students in many subjects, including in SAT prep, to help them prepare for their college education.

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What Is the Scientific Method?

The scientific method is a systematic way of conducting experiments or studies so that you can explore the things you observe in the world and answer questions about them. The scientific method, also known as the hypothetico-deductive method, is a series of steps that can help you accurately describe the things you observe or improve your understanding of them.

Ultimately, your goal when you use the scientific method is to:

• Find a cause-and-effect relationship by asking a question about something you observed
• Collect as much evidence as you can about what you observed, as this can help you explore the connection between your evidence and what you observed
• Determine if all your evidence can be combined to answer your question in a way that makes sense

Francis Bacon and René Descartes are usually credited with formalizing the process in the 16th and 17th centuries. The two philosophers argued that research shouldn’t be guided by preset metaphysical ideas of how reality works. They supported the use of inductive reasoning to come up with hypotheses and understand new things about reality.

Scientific Method Steps

The scientific method is a step-by-step problem-solving process. These steps include:

Observe the world around you. This will help you come up with a topic you are interested in and want to learn more about. In many cases, you already have a topic in mind because you have a related question for which you couldn't find an immediate answer.

Either way, you'll start the process by finding out what people before you already know about the topic, as well as any questions that people are still asking about. You may need to look up and read books and articles from academic journals or talk to other people so that you understand as much as you possibly can about your topic. This will help you with your next step.

Ask questions. Asking questions about what you observed and learned from reading and talking to others can help you figure out what the "problem" is. Scientists try to ask questions that are both interesting and specific and can be answered with the help of a fairly easy experiment or series of experiments. Your question should have one part (called a variable) that you can change in your experiment and another variable that you can measure. Your goal is to design an experiment that is a "fair test," which is when all the conditions in the experiment are kept the same except for the one you change (called the experimental or independent variable).

Form a hypothesis and make predictions based on it.  A hypothesis is an educated guess about the relationship between two or more variables in your question. A good hypothesis lets you predict what will happen when you test it in an experiment. Another important feature of a good hypothesis is that, if the hypothesis is wrong, you should be able to show that it's wrong. This is called falsifiability. If your experiment shows that your prediction is true, then your hypothesis is supported by your data.

Test your prediction by doing an experiment or making more observations.  The way you test your prediction depends on what you are studying. The best support comes from an experiment, but in some cases, it's too hard or impossible to change the variables in an experiment. Sometimes, you may need to do descriptive research where you gather more observations instead of doing an experiment. You will carefully gather notes and measurements during your experiments or studies, and you can share them with other people interested in the same question as you. Ideally, you will also repeat your experiment a couple more times because it's possible to get a result by chance, but it's less possible to get the same result more than once by chance.

Draw a conclusion. You will analyze what you already know about your topic from your literature research and the data gathered during your experiment. This will help you decide if the conclusion you draw from your data supports or contradicts your hypothesis. If your results contradict your hypothesis, you can use this observation to form a new hypothesis and make a new prediction. This is why scientific research is ongoing and scientific knowledge is changing all the time. It's very common for scientists to get results that don't support their hypotheses. In fact, you sometimes learn more about the world when your experiments don't support your hypotheses because it leads you to ask more questions. And this time around, you already know that one possible explanation is likely wrong.

Use your results to guide your next steps (iterate). For instance, if your hypothesis is supported, you may do more experiments to confirm it. Or you could come up with a hypothesis about why it works this way and design an experiment to test that. If your hypothesis is not supported, you can come up with another hypothesis and do experiments to test it. You'll rarely get the right hypothesis in one go. Most of the time, you'll have to go back to the hypothesis stage and try again. Every attempt offers you important information that helps you improve your next round of questions, hypotheses, and predictions.

Share your results. Scientific research isn't something you can do on your own; you must work with other people to do it.   You may be able to do an experiment or a series of experiments on your own, but you can't come up with all the ideas or do all the experiments by yourself .

Scientists and researchers usually share information by publishing it in a scientific journal or by presenting it to their colleagues during meetings and scientific conferences. These journals are read and the conferences are attended by other researchers who are interested in the same questions. If there's anything wrong with your hypothesis, prediction, experiment design, or conclusion, other researchers will likely find it and point it out to you.

It can be scary, but it's a critical part of doing scientific research. You must let your research be examined by other researchers who are as interested and knowledgeable about your question as you. This process helps other researchers by pointing out hypotheses that have been proved wrong and why they are wrong. It helps you by identifying flaws in your thinking or experiment design. And if you don't share what you've learned and let other people ask questions about it, it's not helpful to your or anyone else's understanding of what happens in the world.

Scientific Method Example

Here's an everyday example of how you can apply the scientific method to understand more about your world so you can solve your problems in a helpful way.

Let's say you put slices of bread in your toaster and press the button, but nothing happens. Your toaster isn't working, but you can't afford to buy a new one right now. You might be able to rescue it from the trash can if you can figure out what's wrong with it. So, let's figure out what's wrong with your toaster.

Observation. Your toaster isn't working to toast your bread.

Ask a question. In this case, you're asking, "Why isn't my toaster working?" You could even do a bit of preliminary research by looking in the owner's manual for your toaster. The manufacturer has likely tested your toaster model under many conditions, and they may have some ideas for where to start with your hypothesis.

Form a hypothesis and make predictions based on it. Your hypothesis should be a potential explanation or answer to the question that you can test to see if it's correct. One possible explanation that we could test is that the power outlet is broken. Our prediction is that if the outlet is broken, then plugging it into a different outlet should make the toaster work again.

Test your prediction by doing an experiment or making more observations. You plug the toaster into a different outlet and try to toast your bread.

If that works, then your hypothesis is supported by your experimental data. Results that support your hypothesis don't prove it right; they simply suggest that it's a likely explanation. This uncertainty arises because, in the real world, we can't rule out the possibility of mistakes, wrong assumptions, or weird coincidences affecting the results. If the toaster doesn’t work even after plugging it into a different outlet, then your hypothesis is not supported and it's likely the wrong explanation.

Use your results to guide your next steps (iteration). If your toaster worked, you may decide to do further tests to confirm it or revise it. For example, you could plug something else that you know is working into the first outlet to see if that stops working too. That would be further confirmation that your hypothesis is correct.

If your toaster failed to toast when plugged into the second outlet, you need a new hypothesis. For example, your next hypothesis might be that the toaster has a shorted wire. You could test this hypothesis directly if you have the right equipment and training, or you could take it to a repair shop where they could test that hypothesis for you.

Share your results. For this everyday example, you probably wouldn't want to write a paper, but you could share your problem-solving efforts with your housemates or anyone you hire to repair your outlet or help you test if the toaster has a short circuit.

What the Scientific Method Is Used For

The scientific method is useful whenever you need to reason logically about your questions and gather evidence to support your problem-solving efforts. So, you can use it in everyday life to answer many of your questions; however, when most people think of the scientific method, they likely think of using it to:

Describe how nature works . It can be hard to accurately describe how nature works because it's almost impossible to account for every variable that's involved in a natural process. Researchers may not even know about many of the variables that are involved. In some cases, all you can do is make assumptions. But you can use the scientific method to logically disprove wrong assumptions by identifying flaws in the reasoning.

Do scientific research in a laboratory to develop things such as new medicines.

Develop critical thinking skills.  Using the scientific method may help you develop critical thinking in your daily life because you learn to systematically ask questions and gather evidence to find answers. Without logical reasoning, you might be more likely to have a distorted perspective or bias. Bias is the inclination we all have to favor one perspective (usually our own) over another.

The scientific method doesn't perfectly solve the problem of bias, but it does make it harder for an entire field to be biased in the same direction. That's because it's unlikely that all the people working in a field have the same biases. It also helps make the biases of individuals more obvious because if you repeatedly misinterpret information in the same way in multiple experiments or over a period, the other people working on the same question will notice. If you don't correct your bias when others point it out to you, you'll lose your credibility. Other people might then stop believing what you have to say.

Why Is the Scientific Method Important?

When you use the scientific method, your goal is to do research in a fair, unbiased, and repeatable way. The scientific method helps meet these goals because:

It's a systematic approach to problem-solving. It can help you figure out where you're going wrong in your thinking and research if you're not getting helpful answers to your questions. Helpful answers solve problems and keep you moving forward. So, a systematic approach helps you improve your problem-solving abilities if you get stuck.

It can help you solve your problems.  The scientific method helps you isolate problems by focusing on what's important. In addition, it can help you make your solutions better every time you go through the process.

It helps you eliminate (or become aware of) your personal biases.  It can help you limit the influence of your own personal, preconceived notions . A big part of the process is considering what other people already know and think about your question. It also involves sharing what you've learned and letting other people ask about your methods and conclusions. At the end of the process, even if you still think your answer is best, you have considered what other people know and think about the question.

The scientific method is a systematic way of conducting experiments or studies so that you can explore the world around you and answer questions using reason and evidence. It's a step-by-step problem-solving process that involves: (1) observation, (2) asking questions, (3) forming hypotheses and making predictions, (4) testing your hypotheses through experiments or more observations, (5) using what you learned through experiment or observation to guide further investigation, and (6) sharing your results.

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1.1.6: Scientific Problem Solving

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How can we use problem solving in our everyday routines?

One day you wake up and realize your clock radio did not turn on to get you out of bed. You are puzzled, so you decide to find out what happened. You list three possible explanations:

• There was a power failure and your radio cannot turn on.
• Your little sister turned it off as a joke.
• You did not set the alarm last night.

Upon investigation, you find that the clock is on, so there is no power failure. Your little sister was spending the night with a friend and could not have turned the alarm off. You notice that the alarm is not set—your forgetfulness made you late. You have used the scientific method to answer a question.

Scientific Problem Solving

Humans have always wondered about the world around them. One of the questions of interest was (and still is): what is this world made of? Chemistry has been defined in various ways as the study of matter. What matter consists of has been a source of debate over the centuries. One of the key areas for this debate in the Western world was Greek philosophy.

The basic approach of the Greek philosophers was to discuss and debate the questions they had about the world. There was no gathering of information to speak of, just talking. As a result, several ideas about matter were put forth, but never resolved. The first philosopher to carry out the gathering of data was Aristotle (384-322 B.C.). He recorded many observations on the weather, on plant and animal life and behavior, on physical motions, and a number of other topics. Aristotle could probably be considered the first "real" scientist, because he made systematic observations of nature and tried to understand what he was seeing.

Inductive and Deductive Reasoning

Two approaches to logical thinking developed over the centuries. These two methods are inductive reasoning and deductive reasoning . Inductive reasoning involves getting a collection of specific examples and drawing a general conclusion from them. Deductive reasoning takes a general principle and then draws a specific conclusion from the general concept. Both are used in the development of scientific ideas.

Inductive reasoning first involves the collection of data: "If I add sodium metal to water, I observe a very violent reaction. Every time I repeat the process, I see the same thing happen." A general conclusion is drawn from these observations: the addition of sodium to water results in a violent reaction.

In deductive reasoning, a specific prediction is made based on a general principle. One general principle is that acids turn blue litmus paper red. Using the deductive reasoning process, one might predict: "If I have a bottle of liquid labeled 'acid', I expect the litmus paper to turn red when I immerse it in the liquid."

The Idea of the Experiment

Inductive reasoning is at the heart of what is now called the " scientific method ." In European culture, this approach was developed mainly by Francis Bacon (1561-1626), a British scholar. He advocated the use of inductive reasoning in every area of life, not just science. The scientific method, as developed by Bacon and others, involves several steps:

• Ask a question - identify the problem to be considered.
• Make observations - gather data that pertains to the question.
• Propose an explanation (a hypothesis) for the observations.
• Make new observations to test the hypothesis further.

Note that this should not be considered a "cookbook" for scientific research. Scientists do not sit down with their daily "to do" list and write down these steps. The steps may not necessarily be followed in order. But this does provide a general idea of how scientific research is usually done.

When a hypothesis is confirmed repeatedly, it eventually becomes a theory—a general principle that is offered to explain natural phenomena. Note a key word— explain , or  explanation . A theory offers a description of why something happens. A law, on the other hand, is a statement that is always true, but offers no explanation as to why. The law of gravity says a rock will fall when dropped, but does not explain why (gravitational theory is very complex and incomplete at present). The kinetic molecular theory of gases, on the other hand, states what happens when a gas is heated in a closed container (the pressure increases), but also explains why (the motions of the gas molecules are increased due to the change in temperature). Theories do not get "promoted" to laws, because laws do not answer the "why" question.

• The early Greek philosophers spent their time talking about nature, but did little or no actual exploration or investigation.
• Inductive reasoning - to develop a general conclusion from a collection of observations.
• Deductive reasoning - to make a specific statement based on a general principle.
• Scientific method - a process of observation, developing a hypothesis, and testing that hypothesis.
• What was the basic shortcoming of the Greek philosophers approach to studying the material world?
• How did Aristotle improve the approach?
• Define “inductive reasoning” and give an example.
• Define “deductive reasoning” and give an example.
• What is the difference between a hypothesis and a theory?
• What is the difference between a theory and a law?

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Scientific Method

Science is an enormously successful human enterprise. The study of scientific method is the attempt to discern the activities by which that success is achieved. Among the activities often identified as characteristic of science are systematic observation and experimentation, inductive and deductive reasoning, and the formation and testing of hypotheses and theories. How these are carried out in detail can vary greatly, but characteristics like these have been looked to as a way of demarcating scientific activity from non-science, where only enterprises which employ some canonical form of scientific method or methods should be considered science (see also the entry on science and pseudo-science ). Others have questioned whether there is anything like a fixed toolkit of methods which is common across science and only science. Some reject privileging one view of method as part of rejecting broader views about the nature of science, such as naturalism (Dupré 2004); some reject any restriction in principle (pluralism).

Scientific method should be distinguished from the aims and products of science, such as knowledge, predictions, or control. Methods are the means by which those goals are achieved. Scientific method should also be distinguished from meta-methodology, which includes the values and justifications behind a particular characterization of scientific method (i.e., a methodology) — values such as objectivity, reproducibility, simplicity, or past successes. Methodological rules are proposed to govern method and it is a meta-methodological question whether methods obeying those rules satisfy given values. Finally, method is distinct, to some degree, from the detailed and contextual practices through which methods are implemented. The latter might range over: specific laboratory techniques; mathematical formalisms or other specialized languages used in descriptions and reasoning; technological or other material means; ways of communicating and sharing results, whether with other scientists or with the public at large; or the conventions, habits, enforced customs, and institutional controls over how and what science is carried out.

While it is important to recognize these distinctions, their boundaries are fuzzy. Hence, accounts of method cannot be entirely divorced from their methodological and meta-methodological motivations or justifications, Moreover, each aspect plays a crucial role in identifying methods. Disputes about method have therefore played out at the detail, rule, and meta-rule levels. Changes in beliefs about the certainty or fallibility of scientific knowledge, for instance (which is a meta-methodological consideration of what we can hope for methods to deliver), have meant different emphases on deductive and inductive reasoning, or on the relative importance attached to reasoning over observation (i.e., differences over particular methods.) Beliefs about the role of science in society will affect the place one gives to values in scientific method.

The issue which has shaped debates over scientific method the most in the last half century is the question of how pluralist do we need to be about method? Unificationists continue to hold out for one method essential to science; nihilism is a form of radical pluralism, which considers the effectiveness of any methodological prescription to be so context sensitive as to render it not explanatory on its own. Some middle degree of pluralism regarding the methods embodied in scientific practice seems appropriate. But the details of scientific practice vary with time and place, from institution to institution, across scientists and their subjects of investigation. How significant are the variations for understanding science and its success? How much can method be abstracted from practice? This entry describes some of the attempts to characterize scientific method or methods, as well as arguments for a more context-sensitive approach to methods embedded in actual scientific practices.

1. Overview and organizing themes

2. historical review: aristotle to mill, 3.1 logical constructionism and operationalism, 3.2. h-d as a logic of confirmation, 3.3. popper and falsificationism, 3.4 meta-methodology and the end of method, 4. statistical methods for hypothesis testing, 5.1 creative and exploratory practices.

• 5.2 Computer methods and the ‘new ways’ of doing science

6.1 “The scientific method” in science education and as seen by scientists

6.2 privileged methods and ‘gold standards’, 6.3 scientific method in the court room, 6.4 deviating practices, 7. conclusion, other internet resources, related entries.

This entry could have been given the title Scientific Methods and gone on to fill volumes, or it could have been extremely short, consisting of a brief summary rejection of the idea that there is any such thing as a unique Scientific Method at all. Both unhappy prospects are due to the fact that scientific activity varies so much across disciplines, times, places, and scientists that any account which manages to unify it all will either consist of overwhelming descriptive detail, or trivial generalizations.

The choice of scope for the present entry is more optimistic, taking a cue from the recent movement in philosophy of science toward a greater attention to practice: to what scientists actually do. This “turn to practice” can be seen as the latest form of studies of methods in science, insofar as it represents an attempt at understanding scientific activity, but through accounts that are neither meant to be universal and unified, nor singular and narrowly descriptive. To some extent, different scientists at different times and places can be said to be using the same method even though, in practice, the details are different.

Whether the context in which methods are carried out is relevant, or to what extent, will depend largely on what one takes the aims of science to be and what one’s own aims are. For most of the history of scientific methodology the assumption has been that the most important output of science is knowledge and so the aim of methodology should be to discover those methods by which scientific knowledge is generated.

Science was seen to embody the most successful form of reasoning (but which form?) to the most certain knowledge claims (but how certain?) on the basis of systematically collected evidence (but what counts as evidence, and should the evidence of the senses take precedence, or rational insight?) Section 2 surveys some of the history, pointing to two major themes. One theme is seeking the right balance between observation and reasoning (and the attendant forms of reasoning which employ them); the other is how certain scientific knowledge is or can be.

Section 3 turns to 20 th century debates on scientific method. In the second half of the 20 th century the epistemic privilege of science faced several challenges and many philosophers of science abandoned the reconstruction of the logic of scientific method. Views changed significantly regarding which functions of science ought to be captured and why. For some, the success of science was better identified with social or cultural features. Historical and sociological turns in the philosophy of science were made, with a demand that greater attention be paid to the non-epistemic aspects of science, such as sociological, institutional, material, and political factors. Even outside of those movements there was an increased specialization in the philosophy of science, with more and more focus on specific fields within science. The combined upshot was very few philosophers arguing any longer for a grand unified methodology of science. Sections 3 and 4 surveys the main positions on scientific method in 20 th century philosophy of science, focusing on where they differ in their preference for confirmation or falsification or for waiving the idea of a special scientific method altogether.

In recent decades, attention has primarily been paid to scientific activities traditionally falling under the rubric of method, such as experimental design and general laboratory practice, the use of statistics, the construction and use of models and diagrams, interdisciplinary collaboration, and science communication. Sections 4–6 attempt to construct a map of the current domains of the study of methods in science.

As these sections illustrate, the question of method is still central to the discourse about science. Scientific method remains a topic for education, for science policy, and for scientists. It arises in the public domain where the demarcation or status of science is at issue. Some philosophers have recently returned, therefore, to the question of what it is that makes science a unique cultural product. This entry will close with some of these recent attempts at discerning and encapsulating the activities by which scientific knowledge is achieved.

Attempting a history of scientific method compounds the vast scope of the topic. This section briefly surveys the background to modern methodological debates. What can be called the classical view goes back to antiquity, and represents a point of departure for later divergences. [ 1 ]

We begin with a point made by Laudan (1968) in his historical survey of scientific method:

Perhaps the most serious inhibition to the emergence of the history of theories of scientific method as a respectable area of study has been the tendency to conflate it with the general history of epistemology, thereby assuming that the narrative categories and classificatory pigeon-holes applied to the latter are also basic to the former. (1968: 5)

To see knowledge about the natural world as falling under knowledge more generally is an understandable conflation. Histories of theories of method would naturally employ the same narrative categories and classificatory pigeon holes. An important theme of the history of epistemology, for example, is the unification of knowledge, a theme reflected in the question of the unification of method in science. Those who have identified differences in kinds of knowledge have often likewise identified different methods for achieving that kind of knowledge (see the entry on the unity of science ).

Different views on what is known, how it is known, and what can be known are connected. Plato distinguished the realms of things into the visible and the intelligible ( The Republic , 510a, in Cooper 1997). Only the latter, the Forms, could be objects of knowledge. The intelligible truths could be known with the certainty of geometry and deductive reasoning. What could be observed of the material world, however, was by definition imperfect and deceptive, not ideal. The Platonic way of knowledge therefore emphasized reasoning as a method, downplaying the importance of observation. Aristotle disagreed, locating the Forms in the natural world as the fundamental principles to be discovered through the inquiry into nature ( Metaphysics Z , in Barnes 1984).

Aristotle is recognized as giving the earliest systematic treatise on the nature of scientific inquiry in the western tradition, one which embraced observation and reasoning about the natural world. In the Prior and Posterior Analytics , Aristotle reflects first on the aims and then the methods of inquiry into nature. A number of features can be found which are still considered by most to be essential to science. For Aristotle, empiricism, careful observation (but passive observation, not controlled experiment), is the starting point. The aim is not merely recording of facts, though. For Aristotle, science ( epistêmê ) is a body of properly arranged knowledge or learning—the empirical facts, but also their ordering and display are of crucial importance. The aims of discovery, ordering, and display of facts partly determine the methods required of successful scientific inquiry. Also determinant is the nature of the knowledge being sought, and the explanatory causes proper to that kind of knowledge (see the discussion of the four causes in the entry on Aristotle on causality ).

In addition to careful observation, then, scientific method requires a logic as a system of reasoning for properly arranging, but also inferring beyond, what is known by observation. Methods of reasoning may include induction, prediction, or analogy, among others. Aristotle’s system (along with his catalogue of fallacious reasoning) was collected under the title the Organon . This title would be echoed in later works on scientific reasoning, such as Novum Organon by Francis Bacon, and Novum Organon Restorum by William Whewell (see below). In Aristotle’s Organon reasoning is divided primarily into two forms, a rough division which persists into modern times. The division, known most commonly today as deductive versus inductive method, appears in other eras and methodologies as analysis/​synthesis, non-ampliative/​ampliative, or even confirmation/​verification. The basic idea is there are two “directions” to proceed in our methods of inquiry: one away from what is observed, to the more fundamental, general, and encompassing principles; the other, from the fundamental and general to instances or implications of principles.

The basic aim and method of inquiry identified here can be seen as a theme running throughout the next two millennia of reflection on the correct way to seek after knowledge: carefully observe nature and then seek rules or principles which explain or predict its operation. The Aristotelian corpus provided the framework for a commentary tradition on scientific method independent of science itself (cosmos versus physics.) During the medieval period, figures such as Albertus Magnus (1206–1280), Thomas Aquinas (1225–1274), Robert Grosseteste (1175–1253), Roger Bacon (1214/1220–1292), William of Ockham (1287–1347), Andreas Vesalius (1514–1546), Giacomo Zabarella (1533–1589) all worked to clarify the kind of knowledge obtainable by observation and induction, the source of justification of induction, and best rules for its application. [ 2 ] Many of their contributions we now think of as essential to science (see also Laudan 1968). As Aristotle and Plato had employed a framework of reasoning either “to the forms” or “away from the forms”, medieval thinkers employed directions away from the phenomena or back to the phenomena. In analysis, a phenomena was examined to discover its basic explanatory principles; in synthesis, explanations of a phenomena were constructed from first principles.

During the Scientific Revolution these various strands of argument, experiment, and reason were forged into a dominant epistemic authority. The 16 th –18 th centuries were a period of not only dramatic advance in knowledge about the operation of the natural world—advances in mechanical, medical, biological, political, economic explanations—but also of self-awareness of the revolutionary changes taking place, and intense reflection on the source and legitimation of the method by which the advances were made. The struggle to establish the new authority included methodological moves. The Book of Nature, according to the metaphor of Galileo Galilei (1564–1642) or Francis Bacon (1561–1626), was written in the language of mathematics, of geometry and number. This motivated an emphasis on mathematical description and mechanical explanation as important aspects of scientific method. Through figures such as Henry More and Ralph Cudworth, a neo-Platonic emphasis on the importance of metaphysical reflection on nature behind appearances, particularly regarding the spiritual as a complement to the purely mechanical, remained an important methodological thread of the Scientific Revolution (see the entries on Cambridge platonists ; Boyle ; Henry More ; Galileo ).

In Novum Organum (1620), Bacon was critical of the Aristotelian method for leaping from particulars to universals too quickly. The syllogistic form of reasoning readily mixed those two types of propositions. Bacon aimed at the invention of new arts, principles, and directions. His method would be grounded in methodical collection of observations, coupled with correction of our senses (and particularly, directions for the avoidance of the Idols, as he called them, kinds of systematic errors to which naïve observers are prone.) The community of scientists could then climb, by a careful, gradual and unbroken ascent, to reliable general claims.

Bacon’s method has been criticized as impractical and too inflexible for the practicing scientist. Whewell would later criticize Bacon in his System of Logic for paying too little attention to the practices of scientists. It is hard to find convincing examples of Bacon’s method being put in to practice in the history of science, but there are a few who have been held up as real examples of 16 th century scientific, inductive method, even if not in the rigid Baconian mold: figures such as Robert Boyle (1627–1691) and William Harvey (1578–1657) (see the entry on Bacon ).

It is to Isaac Newton (1642–1727), however, that historians of science and methodologists have paid greatest attention. Given the enormous success of his Principia Mathematica and Opticks , this is understandable. The study of Newton’s method has had two main thrusts: the implicit method of the experiments and reasoning presented in the Opticks, and the explicit methodological rules given as the Rules for Philosophising (the Regulae) in Book III of the Principia . [ 3 ] Newton’s law of gravitation, the linchpin of his new cosmology, broke with explanatory conventions of natural philosophy, first for apparently proposing action at a distance, but more generally for not providing “true”, physical causes. The argument for his System of the World ( Principia , Book III) was based on phenomena, not reasoned first principles. This was viewed (mainly on the continent) as insufficient for proper natural philosophy. The Regulae counter this objection, re-defining the aims of natural philosophy by re-defining the method natural philosophers should follow. (See the entry on Newton’s philosophy .)

To his list of methodological prescriptions should be added Newton’s famous phrase “ hypotheses non fingo ” (commonly translated as “I frame no hypotheses”.) The scientist was not to invent systems but infer explanations from observations, as Bacon had advocated. This would come to be known as inductivism. In the century after Newton, significant clarifications of the Newtonian method were made. Colin Maclaurin (1698–1746), for instance, reconstructed the essential structure of the method as having complementary analysis and synthesis phases, one proceeding away from the phenomena in generalization, the other from the general propositions to derive explanations of new phenomena. Denis Diderot (1713–1784) and editors of the Encyclopédie did much to consolidate and popularize Newtonianism, as did Francesco Algarotti (1721–1764). The emphasis was often the same, as much on the character of the scientist as on their process, a character which is still commonly assumed. The scientist is humble in the face of nature, not beholden to dogma, obeys only his eyes, and follows the truth wherever it leads. It was certainly Voltaire (1694–1778) and du Chatelet (1706–1749) who were most influential in propagating the latter vision of the scientist and their craft, with Newton as hero. Scientific method became a revolutionary force of the Enlightenment. (See also the entries on Newton , Leibniz , Descartes , Boyle , Hume , enlightenment , as well as Shank 2008 for a historical overview.)

Not all 18 th century reflections on scientific method were so celebratory. Famous also are George Berkeley’s (1685–1753) attack on the mathematics of the new science, as well as the over-emphasis of Newtonians on observation; and David Hume’s (1711–1776) undermining of the warrant offered for scientific claims by inductive justification (see the entries on: George Berkeley ; David Hume ; Hume’s Newtonianism and Anti-Newtonianism ). Hume’s problem of induction motivated Immanuel Kant (1724–1804) to seek new foundations for empirical method, though as an epistemic reconstruction, not as any set of practical guidelines for scientists. Both Hume and Kant influenced the methodological reflections of the next century, such as the debate between Mill and Whewell over the certainty of inductive inferences in science.

The debate between John Stuart Mill (1806–1873) and William Whewell (1794–1866) has become the canonical methodological debate of the 19 th century. Although often characterized as a debate between inductivism and hypothetico-deductivism, the role of the two methods on each side is actually more complex. On the hypothetico-deductive account, scientists work to come up with hypotheses from which true observational consequences can be deduced—hence, hypothetico-deductive. Because Whewell emphasizes both hypotheses and deduction in his account of method, he can be seen as a convenient foil to the inductivism of Mill. However, equally if not more important to Whewell’s portrayal of scientific method is what he calls the “fundamental antithesis”. Knowledge is a product of the objective (what we see in the world around us) and subjective (the contributions of our mind to how we perceive and understand what we experience, which he called the Fundamental Ideas). Both elements are essential according to Whewell, and he was therefore critical of Kant for too much focus on the subjective, and John Locke (1632–1704) and Mill for too much focus on the senses. Whewell’s fundamental ideas can be discipline relative. An idea can be fundamental even if it is necessary for knowledge only within a given scientific discipline (e.g., chemical affinity for chemistry). This distinguishes fundamental ideas from the forms and categories of intuition of Kant. (See the entry on Whewell .)

Clarifying fundamental ideas would therefore be an essential part of scientific method and scientific progress. Whewell called this process “Discoverer’s Induction”. It was induction, following Bacon or Newton, but Whewell sought to revive Bacon’s account by emphasising the role of ideas in the clear and careful formulation of inductive hypotheses. Whewell’s induction is not merely the collecting of objective facts. The subjective plays a role through what Whewell calls the Colligation of Facts, a creative act of the scientist, the invention of a theory. A theory is then confirmed by testing, where more facts are brought under the theory, called the Consilience of Inductions. Whewell felt that this was the method by which the true laws of nature could be discovered: clarification of fundamental concepts, clever invention of explanations, and careful testing. Mill, in his critique of Whewell, and others who have cast Whewell as a fore-runner of the hypothetico-deductivist view, seem to have under-estimated the importance of this discovery phase in Whewell’s understanding of method (Snyder 1997a,b, 1999). Down-playing the discovery phase would come to characterize methodology of the early 20 th century (see section 3 ).

Mill, in his System of Logic , put forward a narrower view of induction as the essence of scientific method. For Mill, induction is the search first for regularities among events. Among those regularities, some will continue to hold for further observations, eventually gaining the status of laws. One can also look for regularities among the laws discovered in a domain, i.e., for a law of laws. Which “law law” will hold is time and discipline dependent and open to revision. One example is the Law of Universal Causation, and Mill put forward specific methods for identifying causes—now commonly known as Mill’s methods. These five methods look for circumstances which are common among the phenomena of interest, those which are absent when the phenomena are, or those for which both vary together. Mill’s methods are still seen as capturing basic intuitions about experimental methods for finding the relevant explanatory factors ( System of Logic (1843), see Mill entry). The methods advocated by Whewell and Mill, in the end, look similar. Both involve inductive generalization to covering laws. They differ dramatically, however, with respect to the necessity of the knowledge arrived at; that is, at the meta-methodological level (see the entries on Whewell and Mill entries).

3. Logic of method and critical responses

The quantum and relativistic revolutions in physics in the early 20 th century had a profound effect on methodology. Conceptual foundations of both theories were taken to show the defeasibility of even the most seemingly secure intuitions about space, time and bodies. Certainty of knowledge about the natural world was therefore recognized as unattainable. Instead a renewed empiricism was sought which rendered science fallible but still rationally justifiable.

Analyses of the reasoning of scientists emerged, according to which the aspects of scientific method which were of primary importance were the means of testing and confirming of theories. A distinction in methodology was made between the contexts of discovery and justification. The distinction could be used as a wedge between the particularities of where and how theories or hypotheses are arrived at, on the one hand, and the underlying reasoning scientists use (whether or not they are aware of it) when assessing theories and judging their adequacy on the basis of the available evidence. By and large, for most of the 20 th century, philosophy of science focused on the second context, although philosophers differed on whether to focus on confirmation or refutation as well as on the many details of how confirmation or refutation could or could not be brought about. By the mid-20 th century these attempts at defining the method of justification and the context distinction itself came under pressure. During the same period, philosophy of science developed rapidly, and from section 4 this entry will therefore shift from a primarily historical treatment of the scientific method towards a primarily thematic one.

Advances in logic and probability held out promise of the possibility of elaborate reconstructions of scientific theories and empirical method, the best example being Rudolf Carnap’s The Logical Structure of the World (1928). Carnap attempted to show that a scientific theory could be reconstructed as a formal axiomatic system—that is, a logic. That system could refer to the world because some of its basic sentences could be interpreted as observations or operations which one could perform to test them. The rest of the theoretical system, including sentences using theoretical or unobservable terms (like electron or force) would then either be meaningful because they could be reduced to observations, or they had purely logical meanings (called analytic, like mathematical identities). This has been referred to as the verifiability criterion of meaning. According to the criterion, any statement not either analytic or verifiable was strictly meaningless. Although the view was endorsed by Carnap in 1928, he would later come to see it as too restrictive (Carnap 1956). Another familiar version of this idea is operationalism of Percy William Bridgman. In The Logic of Modern Physics (1927) Bridgman asserted that every physical concept could be defined in terms of the operations one would perform to verify the application of that concept. Making good on the operationalisation of a concept even as simple as length, however, can easily become enormously complex (for measuring very small lengths, for instance) or impractical (measuring large distances like light years.)

Carl Hempel’s (1950, 1951) criticisms of the verifiability criterion of meaning had enormous influence. He pointed out that universal generalizations, such as most scientific laws, were not strictly meaningful on the criterion. Verifiability and operationalism both seemed too restrictive to capture standard scientific aims and practice. The tenuous connection between these reconstructions and actual scientific practice was criticized in another way. In both approaches, scientific methods are instead recast in methodological roles. Measurements, for example, were looked to as ways of giving meanings to terms. The aim of the philosopher of science was not to understand the methods per se , but to use them to reconstruct theories, their meanings, and their relation to the world. When scientists perform these operations, however, they will not report that they are doing them to give meaning to terms in a formal axiomatic system. This disconnect between methodology and the details of actual scientific practice would seem to violate the empiricism the Logical Positivists and Bridgman were committed to. The view that methodology should correspond to practice (to some extent) has been called historicism, or intuitionism. We turn to these criticisms and responses in section 3.4 . [ 4 ]

Positivism also had to contend with the recognition that a purely inductivist approach, along the lines of Bacon-Newton-Mill, was untenable. There was no pure observation, for starters. All observation was theory laden. Theory is required to make any observation, therefore not all theory can be derived from observation alone. (See the entry on theory and observation in science .) Even granting an observational basis, Hume had already pointed out that one could not deductively justify inductive conclusions without begging the question by presuming the success of the inductive method. Likewise, positivist attempts at analyzing how a generalization can be confirmed by observations of its instances were subject to a number of criticisms. Goodman (1965) and Hempel (1965) both point to paradoxes inherent in standard accounts of confirmation. Recent attempts at explaining how observations can serve to confirm a scientific theory are discussed in section 4 below.

The standard starting point for a non-inductive analysis of the logic of confirmation is known as the Hypothetico-Deductive (H-D) method. In its simplest form, a sentence of a theory which expresses some hypothesis is confirmed by its true consequences. As noted in section 2 , this method had been advanced by Whewell in the 19 th century, as well as Nicod (1924) and others in the 20 th century. Often, Hempel’s (1966) description of the H-D method, illustrated by the case of Semmelweiss’ inferential procedures in establishing the cause of childbed fever, has been presented as a key account of H-D as well as a foil for criticism of the H-D account of confirmation (see, for example, Lipton’s (2004) discussion of inference to the best explanation; also the entry on confirmation ). Hempel described Semmelsweiss’ procedure as examining various hypotheses explaining the cause of childbed fever. Some hypotheses conflicted with observable facts and could be rejected as false immediately. Others needed to be tested experimentally by deducing which observable events should follow if the hypothesis were true (what Hempel called the test implications of the hypothesis), then conducting an experiment and observing whether or not the test implications occurred. If the experiment showed the test implication to be false, the hypothesis could be rejected. If the experiment showed the test implications to be true, however, this did not prove the hypothesis true. The confirmation of a test implication does not verify a hypothesis, though Hempel did allow that “it provides at least some support, some corroboration or confirmation for it” (Hempel 1966: 8). The degree of this support then depends on the quantity, variety and precision of the supporting evidence.

Another approach that took off from the difficulties with inductive inference was Karl Popper’s critical rationalism or falsificationism (Popper 1959, 1963). Falsification is deductive and similar to H-D in that it involves scientists deducing observational consequences from the hypothesis under test. For Popper, however, the important point was not the degree of confirmation that successful prediction offered to a hypothesis. The crucial thing was the logical asymmetry between confirmation, based on inductive inference, and falsification, which can be based on a deductive inference. (This simple opposition was later questioned, by Lakatos, among others. See the entry on historicist theories of scientific rationality. )

Popper stressed that, regardless of the amount of confirming evidence, we can never be certain that a hypothesis is true without committing the fallacy of affirming the consequent. Instead, Popper introduced the notion of corroboration as a measure for how well a theory or hypothesis has survived previous testing—but without implying that this is also a measure for the probability that it is true.

Popper was also motivated by his doubts about the scientific status of theories like the Marxist theory of history or psycho-analysis, and so wanted to demarcate between science and pseudo-science. Popper saw this as an importantly different distinction than demarcating science from metaphysics. The latter demarcation was the primary concern of many logical empiricists. Popper used the idea of falsification to draw a line instead between pseudo and proper science. Science was science because its method involved subjecting theories to rigorous tests which offered a high probability of failing and thus refuting the theory.

A commitment to the risk of failure was important. Avoiding falsification could be done all too easily. If a consequence of a theory is inconsistent with observations, an exception can be added by introducing auxiliary hypotheses designed explicitly to save the theory, so-called ad hoc modifications. This Popper saw done in pseudo-science where ad hoc theories appeared capable of explaining anything in their field of application. In contrast, science is risky. If observations showed the predictions from a theory to be wrong, the theory would be refuted. Hence, scientific hypotheses must be falsifiable. Not only must there exist some possible observation statement which could falsify the hypothesis or theory, were it observed, (Popper called these the hypothesis’ potential falsifiers) it is crucial to the Popperian scientific method that such falsifications be sincerely attempted on a regular basis.

The more potential falsifiers of a hypothesis, the more falsifiable it would be, and the more the hypothesis claimed. Conversely, hypotheses without falsifiers claimed very little or nothing at all. Originally, Popper thought that this meant the introduction of ad hoc hypotheses only to save a theory should not be countenanced as good scientific method. These would undermine the falsifiabililty of a theory. However, Popper later came to recognize that the introduction of modifications (immunizations, he called them) was often an important part of scientific development. Responding to surprising or apparently falsifying observations often generated important new scientific insights. Popper’s own example was the observed motion of Uranus which originally did not agree with Newtonian predictions. The ad hoc hypothesis of an outer planet explained the disagreement and led to further falsifiable predictions. Popper sought to reconcile the view by blurring the distinction between falsifiable and not falsifiable, and speaking instead of degrees of testability (Popper 1985: 41f.).

From the 1960s on, sustained meta-methodological criticism emerged that drove philosophical focus away from scientific method. A brief look at those criticisms follows, with recommendations for further reading at the end of the entry.

Thomas Kuhn’s The Structure of Scientific Revolutions (1962) begins with a well-known shot across the bow for philosophers of science:

History, if viewed as a repository for more than anecdote or chronology, could produce a decisive transformation in the image of science by which we are now possessed. (1962: 1)

The image Kuhn thought needed transforming was the a-historical, rational reconstruction sought by many of the Logical Positivists, though Carnap and other positivists were actually quite sympathetic to Kuhn’s views. (See the entry on the Vienna Circle .) Kuhn shares with other of his contemporaries, such as Feyerabend and Lakatos, a commitment to a more empirical approach to philosophy of science. Namely, the history of science provides important data, and necessary checks, for philosophy of science, including any theory of scientific method.

The history of science reveals, according to Kuhn, that scientific development occurs in alternating phases. During normal science, the members of the scientific community adhere to the paradigm in place. Their commitment to the paradigm means a commitment to the puzzles to be solved and the acceptable ways of solving them. Confidence in the paradigm remains so long as steady progress is made in solving the shared puzzles. Method in this normal phase operates within a disciplinary matrix (Kuhn’s later concept of a paradigm) which includes standards for problem solving, and defines the range of problems to which the method should be applied. An important part of a disciplinary matrix is the set of values which provide the norms and aims for scientific method. The main values that Kuhn identifies are prediction, problem solving, simplicity, consistency, and plausibility.

An important by-product of normal science is the accumulation of puzzles which cannot be solved with resources of the current paradigm. Once accumulation of these anomalies has reached some critical mass, it can trigger a communal shift to a new paradigm and a new phase of normal science. Importantly, the values that provide the norms and aims for scientific method may have transformed in the meantime. Method may therefore be relative to discipline, time or place

Feyerabend also identified the aims of science as progress, but argued that any methodological prescription would only stifle that progress (Feyerabend 1988). His arguments are grounded in re-examining accepted “myths” about the history of science. Heroes of science, like Galileo, are shown to be just as reliant on rhetoric and persuasion as they are on reason and demonstration. Others, like Aristotle, are shown to be far more reasonable and far-reaching in their outlooks then they are given credit for. As a consequence, the only rule that could provide what he took to be sufficient freedom was the vacuous “anything goes”. More generally, even the methodological restriction that science is the best way to pursue knowledge, and to increase knowledge, is too restrictive. Feyerabend suggested instead that science might, in fact, be a threat to a free society, because it and its myth had become so dominant (Feyerabend 1978).

An even more fundamental kind of criticism was offered by several sociologists of science from the 1970s onwards who rejected the methodology of providing philosophical accounts for the rational development of science and sociological accounts of the irrational mistakes. Instead, they adhered to a symmetry thesis on which any causal explanation of how scientific knowledge is established needs to be symmetrical in explaining truth and falsity, rationality and irrationality, success and mistakes, by the same causal factors (see, e.g., Barnes and Bloor 1982, Bloor 1991). Movements in the Sociology of Science, like the Strong Programme, or in the social dimensions and causes of knowledge more generally led to extended and close examination of detailed case studies in contemporary science and its history. (See the entries on the social dimensions of scientific knowledge and social epistemology .) Well-known examinations by Latour and Woolgar (1979/1986), Knorr-Cetina (1981), Pickering (1984), Shapin and Schaffer (1985) seem to bear out that it was social ideologies (on a macro-scale) or individual interactions and circumstances (on a micro-scale) which were the primary causal factors in determining which beliefs gained the status of scientific knowledge. As they saw it therefore, explanatory appeals to scientific method were not empirically grounded.

A late, and largely unexpected, criticism of scientific method came from within science itself. Beginning in the early 2000s, a number of scientists attempting to replicate the results of published experiments could not do so. There may be close conceptual connection between reproducibility and method. For example, if reproducibility means that the same scientific methods ought to produce the same result, and all scientific results ought to be reproducible, then whatever it takes to reproduce a scientific result ought to be called scientific method. Space limits us to the observation that, insofar as reproducibility is a desired outcome of proper scientific method, it is not strictly a part of scientific method. (See the entry on reproducibility of scientific results .)

By the close of the 20 th century the search for the scientific method was flagging. Nola and Sankey (2000b) could introduce their volume on method by remarking that “For some, the whole idea of a theory of scientific method is yester-year’s debate …”.

Despite the many difficulties that philosophers encountered in trying to providing a clear methodology of conformation (or refutation), still important progress has been made on understanding how observation can provide evidence for a given theory. Work in statistics has been crucial for understanding how theories can be tested empirically, and in recent decades a huge literature has developed that attempts to recast confirmation in Bayesian terms. Here these developments can be covered only briefly, and we refer to the entry on confirmation for further details and references.

Statistics has come to play an increasingly important role in the methodology of the experimental sciences from the 19 th century onwards. At that time, statistics and probability theory took on a methodological role as an analysis of inductive inference, and attempts to ground the rationality of induction in the axioms of probability theory have continued throughout the 20 th century and in to the present. Developments in the theory of statistics itself, meanwhile, have had a direct and immense influence on the experimental method, including methods for measuring the uncertainty of observations such as the Method of Least Squares developed by Legendre and Gauss in the early 19 th century, criteria for the rejection of outliers proposed by Peirce by the mid-19 th century, and the significance tests developed by Gosset (a.k.a. “Student”), Fisher, Neyman & Pearson and others in the 1920s and 1930s (see, e.g., Swijtink 1987 for a brief historical overview; and also the entry on C.S. Peirce ).

These developments within statistics then in turn led to a reflective discussion among both statisticians and philosophers of science on how to perceive the process of hypothesis testing: whether it was a rigorous statistical inference that could provide a numerical expression of the degree of confidence in the tested hypothesis, or if it should be seen as a decision between different courses of actions that also involved a value component. This led to a major controversy among Fisher on the one side and Neyman and Pearson on the other (see especially Fisher 1955, Neyman 1956 and Pearson 1955, and for analyses of the controversy, e.g., Howie 2002, Marks 2000, Lenhard 2006). On Fisher’s view, hypothesis testing was a methodology for when to accept or reject a statistical hypothesis, namely that a hypothesis should be rejected by evidence if this evidence would be unlikely relative to other possible outcomes, given the hypothesis were true. In contrast, on Neyman and Pearson’s view, the consequence of error also had to play a role when deciding between hypotheses. Introducing the distinction between the error of rejecting a true hypothesis (type I error) and accepting a false hypothesis (type II error), they argued that it depends on the consequences of the error to decide whether it is more important to avoid rejecting a true hypothesis or accepting a false one. Hence, Fisher aimed for a theory of inductive inference that enabled a numerical expression of confidence in a hypothesis. To him, the important point was the search for truth, not utility. In contrast, the Neyman-Pearson approach provided a strategy of inductive behaviour for deciding between different courses of action. Here, the important point was not whether a hypothesis was true, but whether one should act as if it was.

Similar discussions are found in the philosophical literature. On the one side, Churchman (1948) and Rudner (1953) argued that because scientific hypotheses can never be completely verified, a complete analysis of the methods of scientific inference includes ethical judgments in which the scientists must decide whether the evidence is sufficiently strong or that the probability is sufficiently high to warrant the acceptance of the hypothesis, which again will depend on the importance of making a mistake in accepting or rejecting the hypothesis. Others, such as Jeffrey (1956) and Levi (1960) disagreed and instead defended a value-neutral view of science on which scientists should bracket their attitudes, preferences, temperament, and values when assessing the correctness of their inferences. For more details on this value-free ideal in the philosophy of science and its historical development, see Douglas (2009) and Howard (2003). For a broad set of case studies examining the role of values in science, see e.g. Elliott & Richards 2017.

In recent decades, philosophical discussions of the evaluation of probabilistic hypotheses by statistical inference have largely focused on Bayesianism that understands probability as a measure of a person’s degree of belief in an event, given the available information, and frequentism that instead understands probability as a long-run frequency of a repeatable event. Hence, for Bayesians probabilities refer to a state of knowledge, whereas for frequentists probabilities refer to frequencies of events (see, e.g., Sober 2008, chapter 1 for a detailed introduction to Bayesianism and frequentism as well as to likelihoodism). Bayesianism aims at providing a quantifiable, algorithmic representation of belief revision, where belief revision is a function of prior beliefs (i.e., background knowledge) and incoming evidence. Bayesianism employs a rule based on Bayes’ theorem, a theorem of the probability calculus which relates conditional probabilities. The probability that a particular hypothesis is true is interpreted as a degree of belief, or credence, of the scientist. There will also be a probability and a degree of belief that a hypothesis will be true conditional on a piece of evidence (an observation, say) being true. Bayesianism proscribes that it is rational for the scientist to update their belief in the hypothesis to that conditional probability should it turn out that the evidence is, in fact, observed (see, e.g., Sprenger & Hartmann 2019 for a comprehensive treatment of Bayesian philosophy of science). Originating in the work of Neyman and Person, frequentism aims at providing the tools for reducing long-run error rates, such as the error-statistical approach developed by Mayo (1996) that focuses on how experimenters can avoid both type I and type II errors by building up a repertoire of procedures that detect errors if and only if they are present. Both Bayesianism and frequentism have developed over time, they are interpreted in different ways by its various proponents, and their relations to previous criticism to attempts at defining scientific method are seen differently by proponents and critics. The literature, surveys, reviews and criticism in this area are vast and the reader is referred to the entries on Bayesian epistemology and confirmation .

5. Method in Practice

Attention to scientific practice, as we have seen, is not itself new. However, the turn to practice in the philosophy of science of late can be seen as a correction to the pessimism with respect to method in philosophy of science in later parts of the 20 th century, and as an attempted reconciliation between sociological and rationalist explanations of scientific knowledge. Much of this work sees method as detailed and context specific problem-solving procedures, and methodological analyses to be at the same time descriptive, critical and advisory (see Nickles 1987 for an exposition of this view). The following section contains a survey of some of the practice focuses. In this section we turn fully to topics rather than chronology.

A problem with the distinction between the contexts of discovery and justification that figured so prominently in philosophy of science in the first half of the 20 th century (see section 2 ) is that no such distinction can be clearly seen in scientific activity (see Arabatzis 2006). Thus, in recent decades, it has been recognized that study of conceptual innovation and change should not be confined to psychology and sociology of science, but are also important aspects of scientific practice which philosophy of science should address (see also the entry on scientific discovery ). Looking for the practices that drive conceptual innovation has led philosophers to examine both the reasoning practices of scientists and the wide realm of experimental practices that are not directed narrowly at testing hypotheses, that is, exploratory experimentation.

Examining the reasoning practices of historical and contemporary scientists, Nersessian (2008) has argued that new scientific concepts are constructed as solutions to specific problems by systematic reasoning, and that of analogy, visual representation and thought-experimentation are among the important reasoning practices employed. These ubiquitous forms of reasoning are reliable—but also fallible—methods of conceptual development and change. On her account, model-based reasoning consists of cycles of construction, simulation, evaluation and adaption of models that serve as interim interpretations of the target problem to be solved. Often, this process will lead to modifications or extensions, and a new cycle of simulation and evaluation. However, Nersessian also emphasizes that

creative model-based reasoning cannot be applied as a simple recipe, is not always productive of solutions, and even its most exemplary usages can lead to incorrect solutions. (Nersessian 2008: 11)

Thus, while on the one hand she agrees with many previous philosophers that there is no logic of discovery, discoveries can derive from reasoned processes, such that a large and integral part of scientific practice is

the creation of concepts through which to comprehend, structure, and communicate about physical phenomena …. (Nersessian 1987: 11)

Similarly, work on heuristics for discovery and theory construction by scholars such as Darden (1991) and Bechtel & Richardson (1993) present science as problem solving and investigate scientific problem solving as a special case of problem-solving in general. Drawing largely on cases from the biological sciences, much of their focus has been on reasoning strategies for the generation, evaluation, and revision of mechanistic explanations of complex systems.

Addressing another aspect of the context distinction, namely the traditional view that the primary role of experiments is to test theoretical hypotheses according to the H-D model, other philosophers of science have argued for additional roles that experiments can play. The notion of exploratory experimentation was introduced to describe experiments driven by the desire to obtain empirical regularities and to develop concepts and classifications in which these regularities can be described (Steinle 1997, 2002; Burian 1997; Waters 2007)). However the difference between theory driven experimentation and exploratory experimentation should not be seen as a sharp distinction. Theory driven experiments are not always directed at testing hypothesis, but may also be directed at various kinds of fact-gathering, such as determining numerical parameters. Vice versa , exploratory experiments are usually informed by theory in various ways and are therefore not theory-free. Instead, in exploratory experiments phenomena are investigated without first limiting the possible outcomes of the experiment on the basis of extant theory about the phenomena.

The development of high throughput instrumentation in molecular biology and neighbouring fields has given rise to a special type of exploratory experimentation that collects and analyses very large amounts of data, and these new ‘omics’ disciplines are often said to represent a break with the ideal of hypothesis-driven science (Burian 2007; Elliott 2007; Waters 2007; O’Malley 2007) and instead described as data-driven research (Leonelli 2012; Strasser 2012) or as a special kind of “convenience experimentation” in which many experiments are done simply because they are extraordinarily convenient to perform (Krohs 2012).

5.2 Computer methods and ‘new ways’ of doing science

The field of omics just described is possible because of the ability of computers to process, in a reasonable amount of time, the huge quantities of data required. Computers allow for more elaborate experimentation (higher speed, better filtering, more variables, sophisticated coordination and control), but also, through modelling and simulations, might constitute a form of experimentation themselves. Here, too, we can pose a version of the general question of method versus practice: does the practice of using computers fundamentally change scientific method, or merely provide a more efficient means of implementing standard methods?

Because computers can be used to automate measurements, quantifications, calculations, and statistical analyses where, for practical reasons, these operations cannot be otherwise carried out, many of the steps involved in reaching a conclusion on the basis of an experiment are now made inside a “black box”, without the direct involvement or awareness of a human. This has epistemological implications, regarding what we can know, and how we can know it. To have confidence in the results, computer methods are therefore subjected to tests of verification and validation.

The distinction between verification and validation is easiest to characterize in the case of computer simulations. In a typical computer simulation scenario computers are used to numerically integrate differential equations for which no analytic solution is available. The equations are part of the model the scientist uses to represent a phenomenon or system under investigation. Verifying a computer simulation means checking that the equations of the model are being correctly approximated. Validating a simulation means checking that the equations of the model are adequate for the inferences one wants to make on the basis of that model.

A number of issues related to computer simulations have been raised. The identification of validity and verification as the testing methods has been criticized. Oreskes et al. (1994) raise concerns that “validiation”, because it suggests deductive inference, might lead to over-confidence in the results of simulations. The distinction itself is probably too clean, since actual practice in the testing of simulations mixes and moves back and forth between the two (Weissart 1997; Parker 2008a; Winsberg 2010). Computer simulations do seem to have a non-inductive character, given that the principles by which they operate are built in by the programmers, and any results of the simulation follow from those in-built principles in such a way that those results could, in principle, be deduced from the program code and its inputs. The status of simulations as experiments has therefore been examined (Kaufmann and Smarr 1993; Humphreys 1995; Hughes 1999; Norton and Suppe 2001). This literature considers the epistemology of these experiments: what we can learn by simulation, and also the kinds of justifications which can be given in applying that knowledge to the “real” world. (Mayo 1996; Parker 2008b). As pointed out, part of the advantage of computer simulation derives from the fact that huge numbers of calculations can be carried out without requiring direct observation by the experimenter/​simulator. At the same time, many of these calculations are approximations to the calculations which would be performed first-hand in an ideal situation. Both factors introduce uncertainties into the inferences drawn from what is observed in the simulation.

For many of the reasons described above, computer simulations do not seem to belong clearly to either the experimental or theoretical domain. Rather, they seem to crucially involve aspects of both. This has led some authors, such as Fox Keller (2003: 200) to argue that we ought to consider computer simulation a “qualitatively different way of doing science”. The literature in general tends to follow Kaufmann and Smarr (1993) in referring to computer simulation as a “third way” for scientific methodology (theoretical reasoning and experimental practice are the first two ways.). It should also be noted that the debates around these issues have tended to focus on the form of computer simulation typical in the physical sciences, where models are based on dynamical equations. Other forms of simulation might not have the same problems, or have problems of their own (see the entry on computer simulations in science ).

In recent years, the rapid development of machine learning techniques has prompted some scholars to suggest that the scientific method has become “obsolete” (Anderson 2008, Carrol and Goodstein 2009). This has resulted in an intense debate on the relative merit of data-driven and hypothesis-driven research (for samples, see e.g. Mazzocchi 2015 or Succi and Coveney 2018). For a detailed treatment of this topic, we refer to the entry scientific research and big data .

6. Discourse on scientific method

Despite philosophical disagreements, the idea of the scientific method still figures prominently in contemporary discourse on many different topics, both within science and in society at large. Often, reference to scientific method is used in ways that convey either the legend of a single, universal method characteristic of all science, or grants to a particular method or set of methods privilege as a special ‘gold standard’, often with reference to particular philosophers to vindicate the claims. Discourse on scientific method also typically arises when there is a need to distinguish between science and other activities, or for justifying the special status conveyed to science. In these areas, the philosophical attempts at identifying a set of methods characteristic for scientific endeavors are closely related to the philosophy of science’s classical problem of demarcation (see the entry on science and pseudo-science ) and to the philosophical analysis of the social dimension of scientific knowledge and the role of science in democratic society.

One of the settings in which the legend of a single, universal scientific method has been particularly strong is science education (see, e.g., Bauer 1992; McComas 1996; Wivagg & Allchin 2002). [ 5 ] Often, ‘the scientific method’ is presented in textbooks and educational web pages as a fixed four or five step procedure starting from observations and description of a phenomenon and progressing over formulation of a hypothesis which explains the phenomenon, designing and conducting experiments to test the hypothesis, analyzing the results, and ending with drawing a conclusion. Such references to a universal scientific method can be found in educational material at all levels of science education (Blachowicz 2009), and numerous studies have shown that the idea of a general and universal scientific method often form part of both students’ and teachers’ conception of science (see, e.g., Aikenhead 1987; Osborne et al. 2003). In response, it has been argued that science education need to focus more on teaching about the nature of science, although views have differed on whether this is best done through student-led investigations, contemporary cases, or historical cases (Allchin, Andersen & Nielsen 2014)

Although occasionally phrased with reference to the H-D method, important historical roots of the legend in science education of a single, universal scientific method are the American philosopher and psychologist Dewey’s account of inquiry in How We Think (1910) and the British mathematician Karl Pearson’s account of science in Grammar of Science (1892). On Dewey’s account, inquiry is divided into the five steps of

(i) a felt difficulty, (ii) its location and definition, (iii) suggestion of a possible solution, (iv) development by reasoning of the bearing of the suggestions, (v) further observation and experiment leading to its acceptance or rejection. (Dewey 1910: 72)

Similarly, on Pearson’s account, scientific investigations start with measurement of data and observation of their correction and sequence from which scientific laws can be discovered with the aid of creative imagination. These laws have to be subject to criticism, and their final acceptance will have equal validity for “all normally constituted minds”. Both Dewey’s and Pearson’s accounts should be seen as generalized abstractions of inquiry and not restricted to the realm of science—although both Dewey and Pearson referred to their respective accounts as ‘the scientific method’.

Occasionally, scientists make sweeping statements about a simple and distinct scientific method, as exemplified by Feynman’s simplified version of a conjectures and refutations method presented, for example, in the last of his 1964 Cornell Messenger lectures. [ 6 ] However, just as often scientists have come to the same conclusion as recent philosophy of science that there is not any unique, easily described scientific method. For example, the physicist and Nobel Laureate Weinberg described in the paper “The Methods of Science … And Those By Which We Live” (1995) how

The fact that the standards of scientific success shift with time does not only make the philosophy of science difficult; it also raises problems for the public understanding of science. We do not have a fixed scientific method to rally around and defend. (1995: 8)

Interview studies with scientists on their conception of method shows that scientists often find it hard to figure out whether available evidence confirms their hypothesis, and that there are no direct translations between general ideas about method and specific strategies to guide how research is conducted (Schickore & Hangel 2019, Hangel & Schickore 2017)

Reference to the scientific method has also often been used to argue for the scientific nature or special status of a particular activity. Philosophical positions that argue for a simple and unique scientific method as a criterion of demarcation, such as Popperian falsification, have often attracted practitioners who felt that they had a need to defend their domain of practice. For example, references to conjectures and refutation as the scientific method are abundant in much of the literature on complementary and alternative medicine (CAM)—alongside the competing position that CAM, as an alternative to conventional biomedicine, needs to develop its own methodology different from that of science.

Also within mainstream science, reference to the scientific method is used in arguments regarding the internal hierarchy of disciplines and domains. A frequently seen argument is that research based on the H-D method is superior to research based on induction from observations because in deductive inferences the conclusion follows necessarily from the premises. (See, e.g., Parascandola 1998 for an analysis of how this argument has been made to downgrade epidemiology compared to the laboratory sciences.) Similarly, based on an examination of the practices of major funding institutions such as the National Institutes of Health (NIH), the National Science Foundation (NSF) and the Biomedical Sciences Research Practices (BBSRC) in the UK, O’Malley et al. (2009) have argued that funding agencies seem to have a tendency to adhere to the view that the primary activity of science is to test hypotheses, while descriptive and exploratory research is seen as merely preparatory activities that are valuable only insofar as they fuel hypothesis-driven research.

In some areas of science, scholarly publications are structured in a way that may convey the impression of a neat and linear process of inquiry from stating a question, devising the methods by which to answer it, collecting the data, to drawing a conclusion from the analysis of data. For example, the codified format of publications in most biomedical journals known as the IMRAD format (Introduction, Method, Results, Analysis, Discussion) is explicitly described by the journal editors as “not an arbitrary publication format but rather a direct reflection of the process of scientific discovery” (see the so-called “Vancouver Recommendations”, ICMJE 2013: 11). However, scientific publications do not in general reflect the process by which the reported scientific results were produced. For example, under the provocative title “Is the scientific paper a fraud?”, Medawar argued that scientific papers generally misrepresent how the results have been produced (Medawar 1963/1996). Similar views have been advanced by philosophers, historians and sociologists of science (Gilbert 1976; Holmes 1987; Knorr-Cetina 1981; Schickore 2008; Suppe 1998) who have argued that scientists’ experimental practices are messy and often do not follow any recognizable pattern. Publications of research results, they argue, are retrospective reconstructions of these activities that often do not preserve the temporal order or the logic of these activities, but are instead often constructed in order to screen off potential criticism (see Schickore 2008 for a review of this work).

Philosophical positions on the scientific method have also made it into the court room, especially in the US where judges have drawn on philosophy of science in deciding when to confer special status to scientific expert testimony. A key case is Daubert vs Merrell Dow Pharmaceuticals (92–102, 509 U.S. 579, 1993). In this case, the Supreme Court argued in its 1993 ruling that trial judges must ensure that expert testimony is reliable, and that in doing this the court must look at the expert’s methodology to determine whether the proffered evidence is actually scientific knowledge. Further, referring to works of Popper and Hempel the court stated that

ordinarily, a key question to be answered in determining whether a theory or technique is scientific knowledge … is whether it can be (and has been) tested. (Justice Blackmun, Daubert v. Merrell Dow Pharmaceuticals; see Other Internet Resources for a link to the opinion)

But as argued by Haack (2005a,b, 2010) and by Foster & Hubner (1999), by equating the question of whether a piece of testimony is reliable with the question whether it is scientific as indicated by a special methodology, the court was producing an inconsistent mixture of Popper’s and Hempel’s philosophies, and this has later led to considerable confusion in subsequent case rulings that drew on the Daubert case (see Haack 2010 for a detailed exposition).

The difficulties around identifying the methods of science are also reflected in the difficulties of identifying scientific misconduct in the form of improper application of the method or methods of science. One of the first and most influential attempts at defining misconduct in science was the US definition from 1989 that defined misconduct as

fabrication, falsification, plagiarism, or other practices that seriously deviate from those that are commonly accepted within the scientific community . (Code of Federal Regulations, part 50, subpart A., August 8, 1989, italics added)

However, the “other practices that seriously deviate” clause was heavily criticized because it could be used to suppress creative or novel science. For example, the National Academy of Science stated in their report Responsible Science (1992) that it

wishes to discourage the possibility that a misconduct complaint could be lodged against scientists based solely on their use of novel or unorthodox research methods. (NAS: 27)

This clause was therefore later removed from the definition. For an entry into the key philosophical literature on conduct in science, see Shamoo & Resnick (2009).

The question of the source of the success of science has been at the core of philosophy since the beginning of modern science. If viewed as a matter of epistemology more generally, scientific method is a part of the entire history of philosophy. Over that time, science and whatever methods its practitioners may employ have changed dramatically. Today, many philosophers have taken up the banners of pluralism or of practice to focus on what are, in effect, fine-grained and contextually limited examinations of scientific method. Others hope to shift perspectives in order to provide a renewed general account of what characterizes the activity we call science.

One such perspective has been offered recently by Hoyningen-Huene (2008, 2013), who argues from the history of philosophy of science that after three lengthy phases of characterizing science by its method, we are now in a phase where the belief in the existence of a positive scientific method has eroded and what has been left to characterize science is only its fallibility. First was a phase from Plato and Aristotle up until the 17 th century where the specificity of scientific knowledge was seen in its absolute certainty established by proof from evident axioms; next was a phase up to the mid-19 th century in which the means to establish the certainty of scientific knowledge had been generalized to include inductive procedures as well. In the third phase, which lasted until the last decades of the 20 th century, it was recognized that empirical knowledge was fallible, but it was still granted a special status due to its distinctive mode of production. But now in the fourth phase, according to Hoyningen-Huene, historical and philosophical studies have shown how “scientific methods with the characteristics as posited in the second and third phase do not exist” (2008: 168) and there is no longer any consensus among philosophers and historians of science about the nature of science. For Hoyningen-Huene, this is too negative a stance, and he therefore urges the question about the nature of science anew. His own answer to this question is that “scientific knowledge differs from other kinds of knowledge, especially everyday knowledge, primarily by being more systematic” (Hoyningen-Huene 2013: 14). Systematicity can have several different dimensions: among them are more systematic descriptions, explanations, predictions, defense of knowledge claims, epistemic connectedness, ideal of completeness, knowledge generation, representation of knowledge and critical discourse. Hence, what characterizes science is the greater care in excluding possible alternative explanations, the more detailed elaboration with respect to data on which predictions are based, the greater care in detecting and eliminating sources of error, the more articulate connections to other pieces of knowledge, etc. On this position, what characterizes science is not that the methods employed are unique to science, but that the methods are more carefully employed.

Another, similar approach has been offered by Haack (2003). She sets off, similar to Hoyningen-Huene, from a dissatisfaction with the recent clash between what she calls Old Deferentialism and New Cynicism. The Old Deferentialist position is that science progressed inductively by accumulating true theories confirmed by empirical evidence or deductively by testing conjectures against basic statements; while the New Cynics position is that science has no epistemic authority and no uniquely rational method and is merely just politics. Haack insists that contrary to the views of the New Cynics, there are objective epistemic standards, and there is something epistemologically special about science, even though the Old Deferentialists pictured this in a wrong way. Instead, she offers a new Critical Commonsensist account on which standards of good, strong, supportive evidence and well-conducted, honest, thorough and imaginative inquiry are not exclusive to the sciences, but the standards by which we judge all inquirers. In this sense, science does not differ in kind from other kinds of inquiry, but it may differ in the degree to which it requires broad and detailed background knowledge and a familiarity with a technical vocabulary that only specialists may possess.

• Aikenhead, G.S., 1987, “High-school graduates’ beliefs about science-technology-society. III. Characteristics and limitations of scientific knowledge”, Science Education , 71(4): 459–487.
• Allchin, D., H.M. Andersen and K. Nielsen, 2014, “Complementary Approaches to Teaching Nature of Science: Integrating Student Inquiry, Historical Cases, and Contemporary Cases in Classroom Practice”, Science Education , 98: 461–486.
• Anderson, C., 2008, “The end of theory: The data deluge makes the scientific method obsolete”, Wired magazine , 16(7): 16–07
• Arabatzis, T., 2006, “On the inextricability of the context of discovery and the context of justification”, in Revisiting Discovery and Justification , J. Schickore and F. Steinle (eds.), Dordrecht: Springer, pp. 215–230.
• Barnes, J. (ed.), 1984, The Complete Works of Aristotle, Vols I and II , Princeton: Princeton University Press.
• Barnes, B. and D. Bloor, 1982, “Relativism, Rationalism, and the Sociology of Knowledge”, in Rationality and Relativism , M. Hollis and S. Lukes (eds.), Cambridge: MIT Press, pp. 1–20.
• Bauer, H.H., 1992, Scientific Literacy and the Myth of the Scientific Method , Urbana: University of Illinois Press.
• Bechtel, W. and R.C. Richardson, 1993, Discovering complexity , Princeton, NJ: Princeton University Press.
• Berkeley, G., 1734, The Analyst in De Motu and The Analyst: A Modern Edition with Introductions and Commentary , D. Jesseph (trans. and ed.), Dordrecht: Kluwer Academic Publishers, 1992.
• Blachowicz, J., 2009, “How science textbooks treat scientific method: A philosopher’s perspective”, The British Journal for the Philosophy of Science , 60(2): 303–344.
• Bloor, D., 1991, Knowledge and Social Imagery , Chicago: University of Chicago Press, 2 nd edition.
• Boyle, R., 1682, New experiments physico-mechanical, touching the air , Printed by Miles Flesher for Richard Davis, bookseller in Oxford.
• Bridgman, P.W., 1927, The Logic of Modern Physics , New York: Macmillan.
• –––, 1956, “The Methodological Character of Theoretical Concepts”, in The Foundations of Science and the Concepts of Science and Psychology , Herbert Feigl and Michael Scriven (eds.), Minnesota: University of Minneapolis Press, pp. 38–76.
• Burian, R., 1997, “Exploratory Experimentation and the Role of Histochemical Techniques in the Work of Jean Brachet, 1938–1952”, History and Philosophy of the Life Sciences , 19(1): 27–45.
• –––, 2007, “On microRNA and the need for exploratory experimentation in post-genomic molecular biology”, History and Philosophy of the Life Sciences , 29(3): 285–311.
• Carnap, R., 1928, Der logische Aufbau der Welt , Berlin: Bernary, transl. by R.A. George, The Logical Structure of the World , Berkeley: University of California Press, 1967.
• –––, 1956, “The methodological character of theoretical concepts”, Minnesota studies in the philosophy of science , 1: 38–76.
• Carrol, S., and D. Goodstein, 2009, “Defining the scientific method”, Nature Methods , 6: 237.
• Churchman, C.W., 1948, “Science, Pragmatics, Induction”, Philosophy of Science , 15(3): 249–268.
• Cooper, J. (ed.), 1997, Plato: Complete Works , Indianapolis: Hackett.
• Darden, L., 1991, Theory Change in Science: Strategies from Mendelian Genetics , Oxford: Oxford University Press
• Dewey, J., 1910, How we think , New York: Dover Publications (reprinted 1997).
• Douglas, H., 2009, Science, Policy, and the Value-Free Ideal , Pittsburgh: University of Pittsburgh Press.
• Dupré, J., 2004, “Miracle of Monism ”, in Naturalism in Question , Mario De Caro and David Macarthur (eds.), Cambridge, MA: Harvard University Press, pp. 36–58.
• Elliott, K.C., 2007, “Varieties of exploratory experimentation in nanotoxicology”, History and Philosophy of the Life Sciences , 29(3): 311–334.
• Elliott, K. C., and T. Richards (eds.), 2017, Exploring inductive risk: Case studies of values in science , Oxford: Oxford University Press.
• Falcon, Andrea, 2005, Aristotle and the science of nature: Unity without uniformity , Cambridge: Cambridge University Press.
• Feyerabend, P., 1978, Science in a Free Society , London: New Left Books
• –––, 1988, Against Method , London: Verso, 2 nd edition.
• Fisher, R.A., 1955, “Statistical Methods and Scientific Induction”, Journal of The Royal Statistical Society. Series B (Methodological) , 17(1): 69–78.
• Foster, K. and P.W. Huber, 1999, Judging Science. Scientific Knowledge and the Federal Courts , Cambridge: MIT Press.
• Fox Keller, E., 2003, “Models, Simulation, and ‘computer experiments’”, in The Philosophy of Scientific Experimentation , H. Radder (ed.), Pittsburgh: Pittsburgh University Press, 198–215.
• Gilbert, G., 1976, “The transformation of research findings into scientific knowledge”, Social Studies of Science , 6: 281–306.
• Gimbel, S., 2011, Exploring the Scientific Method , Chicago: University of Chicago Press.
• Goodman, N., 1965, Fact , Fiction, and Forecast , Indianapolis: Bobbs-Merrill.
• Haack, S., 1995, “Science is neither sacred nor a confidence trick”, Foundations of Science , 1(3): 323–335.
• –––, 2003, Defending science—within reason , Amherst: Prometheus.
• –––, 2005a, “Disentangling Daubert: an epistemological study in theory and practice”, Journal of Philosophy, Science and Law , 5, Haack 2005a available online . doi:10.5840/jpsl2005513
• –––, 2005b, “Trial and error: The Supreme Court’s philosophy of science”, American Journal of Public Health , 95: S66-S73.
• –––, 2010, “Federal Philosophy of Science: A Deconstruction-and a Reconstruction”, NYUJL & Liberty , 5: 394.
• Hangel, N. and J. Schickore, 2017, “Scientists’ conceptions of good research practice”, Perspectives on Science , 25(6): 766–791
• Harper, W.L., 2011, Isaac Newton’s Scientific Method: Turning Data into Evidence about Gravity and Cosmology , Oxford: Oxford University Press.
• Hempel, C., 1950, “Problems and Changes in the Empiricist Criterion of Meaning”, Revue Internationale de Philosophie , 41(11): 41–63.
• –––, 1951, “The Concept of Cognitive Significance: A Reconsideration”, Proceedings of the American Academy of Arts and Sciences , 80(1): 61–77.
• –––, 1965, Aspects of scientific explanation and other essays in the philosophy of science , New York–London: Free Press.
• –––, 1966, Philosophy of Natural Science , Englewood Cliffs: Prentice-Hall.
• Holmes, F.L., 1987, “Scientific writing and scientific discovery”, Isis , 78(2): 220–235.
• Howard, D., 2003, “Two left turns make a right: On the curious political career of North American philosophy of science at midcentury”, in Logical Empiricism in North America , G.L. Hardcastle & A.W. Richardson (eds.), Minneapolis: University of Minnesota Press, pp. 25–93.
• Hoyningen-Huene, P., 2008, “Systematicity: The nature of science”, Philosophia , 36(2): 167–180.
• –––, 2013, Systematicity. The Nature of Science , Oxford: Oxford University Press.
• Howie, D., 2002, Interpreting probability: Controversies and developments in the early twentieth century , Cambridge: Cambridge University Press.
• Hughes, R., 1999, “The Ising Model, Computer Simulation, and Universal Physics”, in Models as Mediators , M. Morgan and M. Morrison (eds.), Cambridge: Cambridge University Press, pp. 97–145
• Hume, D., 1739, A Treatise of Human Nature , D. Fate Norton and M.J. Norton (eds.), Oxford: Oxford University Press, 2000.
• Humphreys, P., 1995, “Computational science and scientific method”, Minds and Machines , 5(1): 499–512.
• ICMJE, 2013, “Recommendations for the Conduct, Reporting, Editing, and Publication of Scholarly Work in Medical Journals”, International Committee of Medical Journal Editors, available online , accessed August 13 2014
• Jeffrey, R.C., 1956, “Valuation and Acceptance of Scientific Hypotheses”, Philosophy of Science , 23(3): 237–246.
• Kaufmann, W.J., and L.L. Smarr, 1993, Supercomputing and the Transformation of Science , New York: Scientific American Library.
• Knorr-Cetina, K., 1981, The Manufacture of Knowledge , Oxford: Pergamon Press.
• Krohs, U., 2012, “Convenience experimentation”, Studies in History and Philosophy of Biological and BiomedicalSciences , 43: 52–57.
• Kuhn, T.S., 1962, The Structure of Scientific Revolutions , Chicago: University of Chicago Press
• Latour, B. and S. Woolgar, 1986, Laboratory Life: The Construction of Scientific Facts , Princeton: Princeton University Press, 2 nd edition.
• Laudan, L., 1968, “Theories of scientific method from Plato to Mach”, History of Science , 7(1): 1–63.
• Lenhard, J., 2006, “Models and statistical inference: The controversy between Fisher and Neyman-Pearson”, The British Journal for the Philosophy of Science , 57(1): 69–91.
• Leonelli, S., 2012, “Making Sense of Data-Driven Research in the Biological and the Biomedical Sciences”, Studies in the History and Philosophy of the Biological and Biomedical Sciences , 43(1): 1–3.
• Levi, I., 1960, “Must the scientist make value judgments?”, Philosophy of Science , 57(11): 345–357
• Lindley, D., 1991, Theory Change in Science: Strategies from Mendelian Genetics , Oxford: Oxford University Press.
• Lipton, P., 2004, Inference to the Best Explanation , London: Routledge, 2 nd edition.
• Marks, H.M., 2000, The progress of experiment: science and therapeutic reform in the United States, 1900–1990 , Cambridge: Cambridge University Press.
• Mazzochi, F., 2015, “Could Big Data be the end of theory in science?”, EMBO reports , 16: 1250–1255.
• Mayo, D.G., 1996, Error and the Growth of Experimental Knowledge , Chicago: University of Chicago Press.
• McComas, W.F., 1996, “Ten myths of science: Reexamining what we think we know about the nature of science”, School Science and Mathematics , 96(1): 10–16.
• Medawar, P.B., 1963/1996, “Is the scientific paper a fraud”, in The Strange Case of the Spotted Mouse and Other Classic Essays on Science , Oxford: Oxford University Press, 33–39.
• Mill, J.S., 1963, Collected Works of John Stuart Mill , J. M. Robson (ed.), Toronto: University of Toronto Press
• NAS, 1992, Responsible Science: Ensuring the integrity of the research process , Washington DC: National Academy Press.
• Nersessian, N.J., 1987, “A cognitive-historical approach to meaning in scientific theories”, in The process of science , N. Nersessian (ed.), Berlin: Springer, pp. 161–177.
• –––, 2008, Creating Scientific Concepts , Cambridge: MIT Press.
• Newton, I., 1726, Philosophiae naturalis Principia Mathematica (3 rd edition), in The Principia: Mathematical Principles of Natural Philosophy: A New Translation , I.B. Cohen and A. Whitman (trans.), Berkeley: University of California Press, 1999.
• –––, 1704, Opticks or A Treatise of the Reflections, Refractions, Inflections & Colors of Light , New York: Dover Publications, 1952.
• Neyman, J., 1956, “Note on an Article by Sir Ronald Fisher”, Journal of the Royal Statistical Society. Series B (Methodological) , 18: 288–294.
• Nickles, T., 1987, “Methodology, heuristics, and rationality”, in Rational changes in science: Essays on Scientific Reasoning , J.C. Pitt (ed.), Berlin: Springer, pp. 103–132.
• Nicod, J., 1924, Le problème logique de l’induction , Paris: Alcan. (Engl. transl. “The Logical Problem of Induction”, in Foundations of Geometry and Induction , London: Routledge, 2000.)
• Nola, R. and H. Sankey, 2000a, “A selective survey of theories of scientific method”, in Nola and Sankey 2000b: 1–65.
• –––, 2000b, After Popper, Kuhn and Feyerabend. Recent Issues in Theories of Scientific Method , London: Springer.
• –––, 2007, Theories of Scientific Method , Stocksfield: Acumen.
• Norton, S., and F. Suppe, 2001, “Why atmospheric modeling is good science”, in Changing the Atmosphere: Expert Knowledge and Environmental Governance , C. Miller and P. Edwards (eds.), Cambridge, MA: MIT Press, 88–133.
• O’Malley, M., 2007, “Exploratory experimentation and scientific practice: Metagenomics and the proteorhodopsin case”, History and Philosophy of the Life Sciences , 29(3): 337–360.
• O’Malley, M., C. Haufe, K. Elliot, and R. Burian, 2009, “Philosophies of Funding”, Cell , 138: 611–615.
• Oreskes, N., K. Shrader-Frechette, and K. Belitz, 1994, “Verification, Validation and Confirmation of Numerical Models in the Earth Sciences”, Science , 263(5147): 641–646.
• Osborne, J., S. Simon, and S. Collins, 2003, “Attitudes towards science: a review of the literature and its implications”, International Journal of Science Education , 25(9): 1049–1079.
• Parascandola, M., 1998, “Epidemiology—2 nd -Rate Science”, Public Health Reports , 113(4): 312–320.
• Parker, W., 2008a, “Franklin, Holmes and the Epistemology of Computer Simulation”, International Studies in the Philosophy of Science , 22(2): 165–83.
• –––, 2008b, “Computer Simulation through an Error-Statistical Lens”, Synthese , 163(3): 371–84.
• Pearson, K. 1892, The Grammar of Science , London: J.M. Dents and Sons, 1951
• Pearson, E.S., 1955, “Statistical Concepts in Their Relation to Reality”, Journal of the Royal Statistical Society , B, 17: 204–207.
• Pickering, A., 1984, Constructing Quarks: A Sociological History of Particle Physics , Edinburgh: Edinburgh University Press.
• Popper, K.R., 1959, The Logic of Scientific Discovery , London: Routledge, 2002
• –––, 1963, Conjectures and Refutations , London: Routledge, 2002.
• –––, 1985, Unended Quest: An Intellectual Autobiography , La Salle: Open Court Publishing Co..
• Rudner, R., 1953, “The Scientist Qua Scientist Making Value Judgments”, Philosophy of Science , 20(1): 1–6.
• Rudolph, J.L., 2005, “Epistemology for the masses: The origin of ‘The Scientific Method’ in American Schools”, History of Education Quarterly , 45(3): 341–376
• Schickore, J., 2008, “Doing science, writing science”, Philosophy of Science , 75: 323–343.
• Schickore, J. and N. Hangel, 2019, “‘It might be this, it should be that…’ uncertainty and doubt in day-to-day science practice”, European Journal for Philosophy of Science , 9(2): 31. doi:10.1007/s13194-019-0253-9
• Shamoo, A.E. and D.B. Resnik, 2009, Responsible Conduct of Research , Oxford: Oxford University Press.
• Shank, J.B., 2008, The Newton Wars and the Beginning of the French Enlightenment , Chicago: The University of Chicago Press.
• Shapin, S. and S. Schaffer, 1985, Leviathan and the air-pump , Princeton: Princeton University Press.
• Smith, G.E., 2002, “The Methodology of the Principia”, in The Cambridge Companion to Newton , I.B. Cohen and G.E. Smith (eds.), Cambridge: Cambridge University Press, 138–173.
• Snyder, L.J., 1997a, “Discoverers’ Induction”, Philosophy of Science , 64: 580–604.
• –––, 1997b, “The Mill-Whewell Debate: Much Ado About Induction”, Perspectives on Science , 5: 159–198.
• –––, 1999, “Renovating the Novum Organum: Bacon, Whewell and Induction”, Studies in History and Philosophy of Science , 30: 531–557.
• Sober, E., 2008, Evidence and Evolution. The logic behind the science , Cambridge: Cambridge University Press
• Sprenger, J. and S. Hartmann, 2019, Bayesian philosophy of science , Oxford: Oxford University Press.
• Steinle, F., 1997, “Entering New Fields: Exploratory Uses of Experimentation”, Philosophy of Science (Proceedings), 64: S65–S74.
• –––, 2002, “Experiments in History and Philosophy of Science”, Perspectives on Science , 10(4): 408–432.
• Strasser, B.J., 2012, “Data-driven sciences: From wonder cabinets to electronic databases”, Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences , 43(1): 85–87.
• Succi, S. and P.V. Coveney, 2018, “Big data: the end of the scientific method?”, Philosophical Transactions of the Royal Society A , 377: 20180145. doi:10.1098/rsta.2018.0145
• Suppe, F., 1998, “The Structure of a Scientific Paper”, Philosophy of Science , 65(3): 381–405.
• Swijtink, Z.G., 1987, “The objectification of observation: Measurement and statistical methods in the nineteenth century”, in The probabilistic revolution. Ideas in History, Vol. 1 , L. Kruger (ed.), Cambridge MA: MIT Press, pp. 261–285.
• Waters, C.K., 2007, “The nature and context of exploratory experimentation: An introduction to three case studies of exploratory research”, History and Philosophy of the Life Sciences , 29(3): 275–284.
• Weinberg, S., 1995, “The methods of science… and those by which we live”, Academic Questions , 8(2): 7–13.
• Weissert, T., 1997, The Genesis of Simulation in Dynamics: Pursuing the Fermi-Pasta-Ulam Problem , New York: Springer Verlag.
• William H., 1628, Exercitatio Anatomica de Motu Cordis et Sanguinis in Animalibus , in On the Motion of the Heart and Blood in Animals , R. Willis (trans.), Buffalo: Prometheus Books, 1993.
• Winsberg, E., 2010, Science in the Age of Computer Simulation , Chicago: University of Chicago Press.
• Wivagg, D. & D. Allchin, 2002, “The Dogma of the Scientific Method”, The American Biology Teacher , 64(9): 645–646

How to cite this entry . Preview the PDF version of this entry at the Friends of the SEP Society . Look up topics and thinkers related to this entry at the Internet Philosophy Ontology Project (InPhO). Enhanced bibliography for this entry at PhilPapers , with links to its database.

• Blackmun opinion , in Daubert v. Merrell Dow Pharmaceuticals (92–102), 509 U.S. 579 (1993).
• Scientific Method at philpapers. Darrell Rowbottom (ed.).
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show/hide words to know

Biased: when someone presents only one viewpoint. Biased articles do not give all the facts and often mislead the reader.

Conclusion: what a person decides based on information they get through research including experiments.

Method: following a certain set of steps to make something, or find an answer to a question. Like baking a pie or fixing the tire on a bicycle.

Research: looking for answers to questions using tools like the scientific method.

What is the Scientific Method?

If you have ever seen something going on and wondered why or how it happened, you have started down the road to discovery. If you continue your journey, you are likely to guess at some of your own answers for your question. Even further along the road you might think of ways to find out if your answers are correct. At this point, whether you know it or not, you are following a path that scientists call the scientific method. If you do some experiments to see if your answer is correct and write down what you learn in a report, you have pretty much completed everything a scientist might do in a laboratory or out in the field when doing research. In fact, the scientific method works well for many things that don’t usually seem so scientific.

The Flashlight Mystery...

Like a crime detective, you can use the elements of the scientific method to find the answer to everyday problems. For example you pick up a flashlight and turn it on, but the light does not work. You have observed that the light does not work. You ask the question, Why doesn't it work? With what you already know about flashlights, you might guess (hypothesize) that the batteries are dead. You say to yourself, if I buy new batteries and replace the old ones in the flashlight, the light should work. To test this prediction you replace the old batteries with new ones from the store. You click the switch on. Does the flashlight work? No?

What else could be the answer? You go back and hypothesize that it might be a broken light bulb. Your new prediction is if you replace the broken light bulb the flashlight will work. It’s time to go back to the store and buy a new light bulb. Now you test this new hypothesis and prediction by replacing the bulb in the flashlight. You flip the switch again. The flashlight lights up. Success!

If this were a scientific project, you would also have written down the results of your tests and a conclusion of your experiments. The results of only the light bulb hypothesis stood up to the test, and we had to reject the battery hypothesis. You would also communicate what you learned to others with a published report, article, or scientific paper.

More to the Mystery...

Not all questions can be answered with only two experiments. It can often take a lot more work and tests to find an answer. Even when you find an answer it may not always be the only answer to the question. This is one reason that different scientists will work on the same question and do their own experiments.

In our flashlight example, you might never get the light to turn on. This probably means you haven’t made enough different guesses (hypotheses) to test the problem. Were the new batteries in the right way? Was the switch rusty, or maybe a wire is broken. Think of all the possible guesses you could test.

No matter what the question, you can use the scientific method to guide you towards an answer. Even those questions that do not seem to be scientific can be solved using this process. Like with the flashlight, you might need to repeat several of the elements of the scientific method to find an answer. No matter how complex the diagram, the scientific method will include the following pieces in order to be complete.

The elements of the scientific method can be used by anyone to help answer questions. Even though these elements can be used in an ordered manner, they do not have to follow the same order. It is better to think of the scientific method as fluid process that can take different paths depending on the situation. Just be sure to incorporate all of the elements when seeking unbiased answers. You may also need to go back a few steps (or a few times) to test several different hypotheses before you come to a conclusion. Click on the image to see other versions of the scientific method. 

• Observation – seeing, hearing, touching…
• Asking a question – why or how?
• Hypothesis – a fancy name for an educated guess about what causes something to happen.
• Prediction – what you think will happen if…
• Testing – this is where you get to experiment and be creative.
• Conclusion – decide how your test results relate to your predictions.
• Communicate – share your results so others can learn from your work.

Other Parts of the Scientific Method…

Now that you have an idea of how the scientific method works there are a few other things to learn so that you will be able test out your new skills and test your hypotheses.

• Control - A group that is similar to other groups but is left alone so that it can be compared to see what happened to the other groups that are tested.
• Data - the numbers and measurements you get from the test in a scientific experiment.
• Independent variable - a variable that you change as part of your experiment. It is important to only change one independent variable for each experiment. 
• Dependent variable - a variable that changes when the independent variable is changed.
• Controlled Variable - these are variables that you never change in your experiment.

Practicing Observations and Wondering How and Why...

It is really hard not to notice things around us and wonder about them. This is how the scientific method begins, by observing and wondering why and how. Why do leaves on trees in many parts of the world turn from green to red, orange, or yellow and fall to the ground when winter comes? How does a spider move around their web without getting stuck like its victims? Both of these questions start with observing something and asking questions. The next time you see something and ask yourself, “I wonder why that does that, or how can it do that?” try out your new detective skills, and see what answer you can find. 

Try Out Your Detective Skills

Now that you have the basics of the scientific method, why not test your skills? The Science Detectives Training Room will test your problem solving ability. Step inside and see if you can escape the room. While you are there, look around and see what other interesting things might be waiting. We think you find this game a great way to learn the scientific method. In fact, we bet you will discover that you already use the scientific method and didn't even know it.

After you've learned the basics of being a detective, practice those skills in The Case of the Mystery Images . While you are there, pay attention to what's around you as you figure out just what is happening in the mystery photos that surround you.

Ready for your next challenge? Try Science Detectives: Case of the Mystery Images for even more mysteries to solve. Take your scientific abilities one step further by making observations and formulating hypothesis about the mysterious images you find within.

Acknowledgements:  

We thank John Alcock for his feedback and suggestions on this article.

Science Detectives - Mystery Room Escape was produced in partnership with the Arizona Science Education Collaborative (ASEC) and funded by ASU Women & Philanthropy.

Flashlight image via Wikimedia Commons - The Oxygen Team

Read more about: Using the Scientific Method to Solve Mysteries

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• Article: Using the Scientific Method to Solve Mysteries
• Author(s): CJ Kazilek and David Pearson
• Publisher: Arizona State University School of Life Sciences Ask A Biologist
• Site name: ASU - Ask A Biologist
• Date published: October 8, 2009
• Date accessed: June 10, 2024
• Link: https://askabiologist.asu.edu/explore/scientific-method

CJ Kazilek and David Pearson. (2009, October 08). Using the Scientific Method to Solve Mysteries . ASU - Ask A Biologist. Retrieved June 10, 2024 from https://askabiologist.asu.edu/explore/scientific-method

Chicago Manual of Style

CJ Kazilek and David Pearson. "Using the Scientific Method to Solve Mysteries ". ASU - Ask A Biologist. 08 October, 2009. https://askabiologist.asu.edu/explore/scientific-method

MLA 2017 Style

CJ Kazilek and David Pearson. "Using the Scientific Method to Solve Mysteries ". ASU - Ask A Biologist. 08 Oct 2009. ASU - Ask A Biologist, Web. 10 Jun 2024. https://askabiologist.asu.edu/explore/scientific-method

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How to Use the Scientific Method in Everyday Life

How to Set Up a Controlled Science Experiment

The scientific method is a procedure consisting of a series of steps with the goal of problem-solving and information-gathering. The scientific method begins with the recognition of a problem and a clear elaboration or description of the problem itself. A process of experimentation and data collection then follows. The final steps consist of the formulation and testing of a hypothesis or potential solution and conclusion. For people unaccustomed to using the scientific method, the process may seem abstract and unapproachable. With a little consideration and observation, any problem encountered in daily life is a potential possibility to use the scientific method.

Locate or identify a problem to solve. Your personal environment is a good place to start, either in the workplace, the home, or your town or city.

Describe the problem in detail. Make quantifiable observations, such as number of times of occurrence, duration, specific physical measurements, and so on.

Form a hypothesis about what the possible cause of the problem might be, or what a potential solution could be. Check if the previously collected data suggests a pattern or possible cause.

Test your hypothesis either through further observation of the problem or by creating an experiment that highlights the aspect of the problem you wish to test. For example, if you suspect a faulty wire is the cause of a light not working, you must find a way to isolate and test whether or not the wire is actually the cause.

Repeat the steps of observation, hypothesis formation and testing until you reach a conclusion that is reinforced by supporting data or directly solves the problem at hand.

• The scientific method is best suited to solving problems without direct or simple answers. For example, a light bulb that burns out may simply need to be replaced. A light bulb that works intermittently is a much more suitable candidate for use of the scientific method, because of all of the potential causes of it not working.

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• Britannica Online Encyclopedia: Scientific Method; June 2011

About the Author

Alex Jakubik began his writing career in 2000 with book-cover summaries for Barnes & Noble. He has also authored concert programs and travel blogs, and worked both nationally and internationally in the arts. Jakubik holds a Bachelor of Music degree from Indiana University and a Master of Music from Yale University.

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Solving Everyday Problems with the Scientific Method: Thinking Like a Scientist (Second Edition) This book describes how one can use The Scientific Method to solve everyday problems including medical ailments, health issues, money management, traveling, shopping, cooking, household chores, etc. It illustrates how to exploit the information collected from our five senses, how to solve problems when no information is available for the present problem situation, how to increase our chances of success by redefining a problem, and how to extrapolate our capabilities by seeing a relationship among heretofore unrelated concepts. One should formulate a hypothesis as early as possible in order to have a sense of direction regarding which path to follow. Occasionally, by making wild conjectures, creative solutions can transpire. However, hypotheses need to be well-tested. Through this way, The Scientific Method can help readers solve problems in both familiar and unfamiliar situations. Containing real-life examples of how various problems are solved — for instance, how some observant patients cure their own illnesses when medical experts have failed — this book will train readers to observe what others may have missed and conceive what others may not have contemplated. With practice, they will be able to solve more problems than they could previously imagine. In this second edition, the authors have added some more theories which they hope can help in solving everyday problems. At the same time, they have updated the book by including quite a few examples which they think are interesting. Readership: General public interested in self-help books; undergraduates majoring in education and behavioral psychology; graduates and researchers with research interests in problem solving, creativity and scientific research methodology. There are no customer reviews for this item yet. Classic Totes Tote bags and pouches in a variety of styles, sizes, and designs , plus mugs, bookmarks, and more! Shipping & Pickup We ship anywhere in the U.S. and orders of $75+ ship free via media mail! Noteworthy Signed Books: Join the Club! Join our Signed First Edition Club (or give a gift subscription) for a signed book of great literary merit, delivered to you monthly. Harvard Square's Independent Bookstore © 2024 Harvard Book Store All rights reserved Contact Harvard Book Store 1256 Massachusetts Avenue Cambridge, MA 02138 Tel (617) 661-1515 Toll Free (800) 542-READ Email [email protected] View our current hours » Join our bookselling team » We plan to remain closed to the public for two weeks, through Saturday, March 28 While our doors are closed, we plan to staff our phones, email, and harvard.com web order services from 10am to 6pm daily. Store Hours Monday - Saturday: 9am - 11pm Sunday: 10am - 10pm Holiday Hours 12/24: 9am - 7pm 12/25: closed 12/31: 9am - 9pm 1/1: 12pm - 11pm All other hours as usual. Map Find Harvard Book Store » Online Customer Service Shipping » Online Returns » Privacy Policy » Harvard University harvard.edu » Clubs & Services Identifying a Scientific Problem Amy has a master's degree in secondary education and has been teaching math for over 9 years. Amy has worked with students at all levels from those with special needs to those that are gifted. Christianlly has taught college Physics, Natural science, Earth science, and facilitated laboratory courses. He has a master's degree in Physics and is currently pursuing his doctorate degree. Table of Contents Identifying a problem, conducting an experiment, the most appropriate solution, lesson summary. Picture yourself playing with a ball. You throw it up, and you watch it fall back down. You climb up a tree, and you let the ball roll off a branch and then down to the grass. Of course, you make sure that nobody is underneath. As you're bending over to roll the ball off the branch, you see that the marble in your pocket also rolls off the branch and down to the grass at the same time your ball does. Interestingly, both the marble and your ball, which is much bigger, reach the grass at the same time. You'd think that since the ball is much bigger, it would hit the ground first. But now, the tiny marble hits the ground at the same time. Will this be true for all things that you drop? Ah, you have a problem. To unlock this lesson you must be a Study.com Member. Create your account An error occurred trying to load this video. Try refreshing the page, or contact customer support. You must c C reate an account to continue watching Register to view this lesson. As a member, you'll also get unlimited access to over 88,000 lessons in math, English, science, history, and more. Plus, get practice tests, quizzes, and personalized coaching to help you succeed. Get unlimited access to over 88,000 lessons. Already registered? Log in here for access Resources created by teachers for teachers. I would definitely recommend Study.com to my colleagues. It’s like a teacher waved a magic wand and did the work for me. I feel like it’s a lifeline. You're on a roll. Keep up the good work! Just checking in. are you still watching. 0:04 Identifying a Problem 0:47 Identifying a… 1:33 Conducting an Experiment 2:33 The Most Appropriate Solution 4:37 Lesson Summary If your problem is a scientific problem, then you can perform a scientific experiment to find the answer to your problem. A scientific problem is a question that you have that can be answered via an experiment. Not all problems that you have are scientific problems. That's because not all questions can be answered with an experiment. For example, the problem of trying to figure out what to have for dinner isn't a scientific problem, since you can't conduct an experiment to find the answer. But the problem of trying to figure out how fast a population of rabbits can grow is a scientific problem as you can conduct an experiment on a population of rabbits to observe and record just how fast they reproduce. You can then use your information and any patterns that you find to find your answer. Once you've determined that your problem is indeed a scientific one, you now need to figure out what kind of experiment to conduct. Your experiment needs to focus on your question and must be repeatable by others. You have one control, the one part of your experiment that you compare your other results to, and then you have your variables or test subjects that you compare to your control. What you observe is then recorded or written down for analysis and to find your answer. For your dropped things question, you can set up an experiment by recording the time it takes for different objects to fall the same distance down to the ground. Your ball is your control. You'll first record the time it takes for your ball to fall to the ground. Then you'll record the time for various other objects to fall to the ground. For example, you might try a tiny marble again. Then you might try a stuffed animal, then perhaps a tiny needle. The more objects you use, the better your experiment will be and the more information you'll have to find your answer. Once you're done with your experiment, and you are analyzing your data, it's possible that you might find several solutions to your problem. For example, from your rabbits' experiment, you might find that the rabbit population in the desert grows much slower than the rabbit population on a tropical island. You have two possible solutions to your answer here (one for your desert population and another for your tropical island population), and you need to find the most appropriate solution. How do you go about doing that? When you have several different solutions from your experiment, you then need to consider if there are other factors at work here. Once you've determined if there are any other external factors that could be changing your solution, you can then find your best solution from there. For the rabbit population experiment, your best solution may be averaging your data from your different sources. Going back to your dropping things experiment, you find that for most items, they all fall at the same time. But for some items, like feathers and pieces of paper, they fall at a much slower rate. So, here again, you have two possible solutions (your items falling at the same rate or items fall at different rates depending on what kind of item it is). Which one gives you the most appropriate answer? Just like in the rabbit population experiment, you'll have to determine if there are external factors at work here too. In this case, you determine that yes, there is indeed an external factor at work. With these items that show a slower rate of falling, you find that these items react much more to air. Feathers are naturally light and float in the air with just a little updraft. Flat pieces of paper likewise float with an updraft. That's why you can throw a paper airplane and watch it glide across a room. From this analysis then, you decide that you can ignore one solution to your problem due to an external factor influencing the fall rate. Your most appropriate solution for your dropping things question is that yes, all things fall at the same rate no matter how large, small, heavy, or light they are. All right, let's take a moment to review. In this lesson, we learned about scientific problems. We learned that a scientific problem is a question that you have that can be answered via an experiment. Once you've determined that your problem is indeed a scientific one, you can then conduct an experiment. Your experiment needs to focus on your question and must be repeatable by others. You have one control, the one part of your experiment that you compare your other results to and then you have your variables or test subjects that you compare to your control. Once you've conducted your experiment, you then analyze your data. You may find several possible answers from your analysis. You'll then need to determine if there are external factors at work. If there are, you'll need to consider if these external factors can be ignored to find your best answer or if you need to incorporate them into your best solution. Scientific Problem: Identification Exercise This activity will check your knowledge regarding the properties of a scientific problem. Identify whether the given statements/questions refer to a scientific problem. To do this, you must right-click and print this page. With a pencil and an eraser, neatly write SCIENTIFIC or NOT SCIENTIFIC in the blank space provided. _______________ 1. What is the origin of the word clairvoyant ? _______________ 2. Henry wants to know the reason why his motorcycle doesn't start. _______________ 3. How to determine the boiling point and the melting point of mercury? _______________ 4. What is the acceleration of an apple as it falls from a tree? _______________ 5. How can one convert Eastern Standard Time to British Summer Time? _______________ 6. Jess tries to determine the longitude and latitude of a country. _______________ 7. What is the current world population today? _______________ 8. Luis ponders on the probability that a 5 is obtained after flipping a dice. _______________ 9. When did the scientific revolution start? _______________ 10. What is the rate at which ice melts when placed at room temperature? NOT SCIENTIFIC Unlock Your Education See for yourself why 30 million people use study.com, become a study.com member and start learning now.. Already a member? Log In Recommended Lessons and Courses for You Related lessons, related courses, recommended lessons for you. Identifying a Scientific Problem Related Study Materials Related Topics Browse by Courses Glencoe Chemistry - Matter And Change: Online Textbook Help Praxis Chemistry: Content Knowledge (5245) Prep CSET Science Subtest II Life Sciences (217): Practice Test & Study Guide Environmental Science 101: Environment and Humanity AP Biology: Exam Prep Prentice Hall Earth Science: Online Textbook Help Anatomy and Physiology: Certificate Program Microbiology: Help and Review DSST Health and Human Development Prep College Chemistry: Certificate Program UExcel Basic Genetics: Study Guide & Test Prep Principles of Physical Science: Certificate Program DSST Principles of Physical Science: Study Guide & Test Prep Middle School Earth Science: Homework Help Resource Middle School Physical Science: Homework Help Resource Browse by Lessons Scientific Method | Definition, Steps & Examples Scientific Investigation | Overview, Steps & Examples Scientific Research Definition, Classifications & Purpose How to Improve Validity of a Scientific Investigation Nonscientific and Scientific Research: Definitions and Differences The Scientific Method Applied to Environmental Problems: Definition, Steps and Applications Scientific Method in Psychology | Definition, Steps & Examples Scientific Experiment | Types & Examples Scientific Thinking Definition, Method & Examples Scientific Method | Overview, Steps & Examples Scientific Method & Observation | Definition, Steps & Examples Scientific Method Lesson for Kids: Definition & Examples Scientific Method Lesson for Kids: Steps & Process Scientific Method Applications to Human Growth and Development Research Scientific Questions | Characteristics & Examples Create an account to start this course today Used by over 30 million students worldwide Create an account Explore our library of over 88,000 lessons Foreign Language Social Science See All College Courses Common Core High School See All High School Courses College & Career Guidance Courses College Placement Exams Entrance Exams General Test Prep K-8 Courses Skills Courses Teacher Certification Exams See All Other Courses Create a Goal Create custom courses Get your questions answered If you're seeing this message, it means we're having trouble loading external resources on our website. If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked. To log in and use all the features of Khan Academy, please enable JavaScript in your browser. Biology library Course: biology library   >   unit 1, the scientific method. Controlled experiments The scientific method and experimental design Introduction Make an observation. Ask a question. Form a hypothesis , or testable explanation. Make a prediction based on the hypothesis. Test the prediction. Iterate: use the results to make new hypotheses or predictions. Scientific method example: Failure to toast 1. make an observation., 2. ask a question., 3. propose a hypothesis., 4. make predictions., 5. test the predictions.. If the toaster does toast, then the hypothesis is supported—likely correct. If the toaster doesn't toast, then the hypothesis is not supported—likely wrong. Logical possibility Practical possibility, building a body of evidence, 6. iterate.. If the hypothesis was supported, we might do additional tests to confirm it, or revise it to be more specific. For instance, we might investigate why the outlet is broken. If the hypothesis was not supported, we would come up with a new hypothesis. For instance, the next hypothesis might be that there's a broken wire in the toaster. Want to join the conversation? Upvote Button navigates to signup page Downvote Button navigates to signup page Flag Button navigates to signup page Advertisement How the Scientific Method Works Share Content on Facebook Share Content on LinkedIn Share Content on Flipboard Share Content on Reddit Share Content via Email Limitations of the Scientific Method Clearly, the scientific method is a powerful tool, but it does have its limitations. These limitations are based on the fact that a hypothesis must be testable and falsifiable and that experiments and observations be repeatable. This places certain topics beyond the reach of the scientific method. Science cannot prove or refute the existence of God or any other supernatural entity. Sometimes, scientific principles are used to try to lend credibility to certain nonscientific ideas, such as intelligent design . Intelligent design is the assertion that certain aspects of the origin of the universe and life can be explained only in the context of an intelligent, divine power. Proponents of intelligent design try to pass this concept off as a scientific theory to make it more palatable to developers of public school curriculums. But intelligent design is not science because the existence of a divine being cannot be tested with an experiment. Science is also incapable of making value judgments. It cannot say global warming is bad, for example. It can study the causes and effects of global warming and report on those results, but it cannot assert that driving SUVs is wrong or that people who haven't replaced their regular light bulbs with LED bulbs are irresponsible. Occasionally, certain organizations use scientific data to advance their causes. This blurs the line between science and morality and encourages the creation of "pseudo-science," which tries to legitimize a product or idea with a claim that has not been subjected to rigorous testing. And yet, used properly, the scientific method is one of the most valuable tools humans have ever created. It helps us solve everyday problems around the house and, at the same time, helps us understand profound questions about the world and universe in which we live. Most of the time, two competing theories can't exist to describe one phenomenon. But in the case of light , one theory is not enough. Many experiments support the notion that light behaves like a longitudinal wave. Taken collectively, these experiments have given rise to the wave theory of light. Other experiments, however, support the notion that light behaves as a particle. Instead of throwing out one theory and keeping the other, physicists maintain a wave/particle duality to describe the behavior of light. Related Articles How Evolution Works Who was James Webb? 10 Scientific Words You're Probably Using Wrong 10 Hispanic Scientists You Should Know How Intelligent Design Works How Occam's Razor Works How Telescopes Work How Hubble Space Telescope Works How Light Microscopes Work How Special Relativity Works ­How Geniuses Work More Great Links Science Fair Project Resource Guide Understanding and Using the Scientific Method The Scientific Method Audubon, John James. "John James Audubon: Writings and Drawings." Library of America, 1999. Campbell, Neil A. and Jane B. Reece. "Biology, Seventh Edition." Pearson Benjamin Cummings, San Francisco, 2005. D'Agnese, Joseph. "Scientific Method Man." Wired, September 2004. http://www.wired.com/wired/archive/12.09/rugg.html. Introduction to the Scientific Method on Web Site of Frank Wolfs, Department of Physics and Astronomy, University of Rochester. http://teacher.pas.rochester.edu/phy_labs/AppendixE/AppendixE.html Keeton, William T. "Biological Science, Third Edition." W.W. Norton & Company, New York, 1980. The New Oxford American Dictionary. Oxford University Press, Oxford, United Kingdom. 2001. Understanding and Using the Scientific Method on Fact Monster. http://www.factmonster.com/cig/science-fair-projects/understanding-using-scientific-method.html Vecchione, Glen. "100 Amazing Award-Winning Science Fair Projects." Sterling Publishing Co., New York, 2001. Vecchione, Glen. "100 Amazing First Prize Science Fair Projects." Sterling Publishing Co., New York, 1998. Please copy/paste the following text to properly cite this HowStuffWorks.com article: The Scientific Revolution Please enter your email address to receive a download link for this resource: Please check your email for the download link. Before class, students will be asked to read two World History Encyclopedia articles. Introduction (10-15 minutes) Hook: Start with a thought-provoking question: "How would you determine whether something is true or not? What process would you use?" Write students’ responses on the board to highlight different approaches, such as personal experience, advice from others, intuition, or logical reasoning. Explain that before the Scientific Revolution , people often relied on methods like tradition, philosophical reasoning, or religious teachings to determine the truth. Introduce the idea that the Scientific Method emerged as a new approach to discovering truth, emphasizing that this method is based on observation, experimentation, and evidence rather than solely on abstract reasoning or accepted beliefs. Hands-On Activity (25-30 minutes) Present the following scenario to the class: "A farmer notices that some crops in his field are growing poorly while others are thriving. He wants to understand why this is happening." Divide the class into an even number of small groups. Half of the groups will receive Handout 1: Philosophical Approach and the other half will receive Handout 2: Scientific Method Approach. Instruct each group to brainstorm solutions to the farmer's problem based on their assigned approach. Philosophical Approach: Groups might suggest reasons based on general principles, such as the alignment of the stars, the will of the gods, or moral interpretations of natural events. Scientific Method Approach: Groups should focus on making specific observations, forming testable hypotheses, designing experiments, and collecting data. Pair each Philosophical Approach group with a Scientific Method Approach group. Have the paired groups present their ideas to each other. Encourage them to discuss and debate the differences between the philosophical reasoning and the scientific method. Class Discussion and Reflection (15-20 minutes) Reflect on the activity, highlighting the strengths and limitations of each approach and the importance of the Scientific Method in advancing knowledge and solving problems. Summarize key takeaways from the lesson, emphasizing how the Scientific Method has led to a more systematic and evidence-based approach to knowledge. Reflect on how the Scientific Method has shaped modern knowledge and technology and ask students how they might use the Scientific Method in their own lives or future careers. Homework/Extension Students will pick one scientist from the collection of 12 Great Scientists of the Scientific Revolution , read their biography, and answer questions on the worksheet (see below). If needed, further research can be done to complete the worksheet. About the Author Free for the World, Supported by You World History Encyclopedia is a non-profit organization. For only $5 per month you can become a member and support our mission to engage people with cultural heritage and to improve history education worldwide. License & Copyright Uploaded by Taleen Aktorosian , published on 28 May 2024. The copyright holder has published this content under the following license: Creative Commons Attribution-NonCommercial-ShareAlike . This license lets others remix, tweak, and build upon this content non-commercially, as long as they credit the author and license their new creations under the identical terms. When republishing on the web a hyperlink back to the original content source URL must be included. Please note that content linked from this page may have different licensing terms. About & FAQ What is a Cult? Public Speaking Critical Merchandise Books I Recommend Become a Patron Curriculum Vitae Using the Scientific Method in Everyday Life by Chris Shelton December 18, 2013 January 6, 2022 Science is not just for Scientists Critical thinking skills are very important for getting along in life. They allow you to analyze  problems or situations you find yourself involved in that don’t always have an easy or obvious answer. We all run into problems in relationships, work, school, etc. Wouldn’t it be easier if we could understand why things were happening around us and more easily see what we could do about them? That’s what critical thinking is all about. It’s not just for winning arguments! In my last article, I mentioned the scientific method. The scientific method is just the steps any scientist takes to solve problems or discover new things. But it’s not just for scientists. And just because it has the word “scientific” in it, doesn’t mean that it’s hard to understand or use. In fact, you most likely already use the scientific method all the time. But like any skill, it is something that can be greatly improved through conscientious practice. Scientific method can be described in different ways and some people include slightly different steps, but basically it comes down to these: 1. Make observations. Looking is the first and most important step. Whether it’s noticing something odd or interesting, or whether you are confronted with a problem of some kind, the first thing you do is observe. Observation doesn’t take place just because of something unusual or odd. You can easily observe what is going on around you anytime. Stop reading this for a moment and look up at the space around you. Notice something you may never have noticed before, or see if there is anything in the environment around you that is different from what you remember the last time you looked around. That is observation. The word “observation” is used rather than “looking” because observing is not just done with the eyes. Visual observation is important, but it can also include any of your senses. Walking into a room and smelling something bad is observation. Hearing a ringing sound coming from a machine or feeling warm air coming off a hot pad are perfectly valid observations. It also can involve using instruments or measuring devices. It’s kind of hard to see with the naked eye that something is 5.498 centimeters wide. Having a measuring device helps in the accuracy of the observation. Using a telescope to observe a distant planet or a microscope to observe cellular behavior is the only way we can even be aware of these things. Observing, by the way, is something that you do on purpose, it’s not passive. You can’t observe something when you are putting up some “mental picture” of what you’ve always seen there every single day instead of seeing what is really there right now in this moment. People do this all the time. It’s not unusual at all for someone to be looking right into an intersection and not “see” the person on a motorcycle twenty feet away. They aren’t really observing what is going on in front of them. Instead, they are “seeing” the same thing they always see when they cross this same intersection on their way home from work every day. Their mind is on other things. And it’s one reason people miss things that are perfectly obvious to other people around them. Observation is a skill you can practice all by itself. And it should be practiced every day. 2. Propose a hypothesis. A hypothesis is an idea or a proposition that explains an observation. It is not necessarily true, but it’s a starting point. It’s basically a guess as to why a particular observation is the way it is. It’s now up to the person who made the hypothesis to find evidence to prove whether it’s true or not. In real life, outside of science, many people will guess or dream up explanations or answers and then stop right there. They’ll assume that what they came up with is true because it’s the best answer they could come up with based on the information available to them at the time. Until you have some proof and have verified the hypothesis is correct, it’s just as likely that it’s not true and you could end up making a really big mistake. So it’s very important to realize that a hypothesis is not the end of critical thinking – it’s just the beginning. An example of a hypothesis you could propose would be something about the weather. Here we are in the middle of December. You are inside and you see that it’s crystal clear outside, the sun is shining brightly with no clouds. There appears to be a slight breeze blowing. You hate having to bundle up every time you want to go outside, so you think to yourself that perhaps today it’s not really so cold out. How could it be when it’s so clear and beautiful? You propose a hypothesis that the temperature outside is tolerable and won’t require you to multi-layer two shirts, a sweater and your parka just to get out to your car so you can drive to work.This could just be wishful thinking, so before you act on it,  you first have to test that hypothesis. 3. Design and perform an experiment to test the hypothesis. An experiment is simply anything that is done to test whether a hypothesis proves out to be true or false. Experiments can be simple, like just taking a measurement of something to see if it’s the amount you think it is. They can also be very complicated, such as injecting a new medicine into thousands of people and carefully monitoring the results as well as monitoring injections of a placebo (a fake medicine) into a similar group of people to see what happens to them too. By comparing the results of the real medicine to the fake medicine, you can test its effectiveness. The most important thing about experimentation is testing your hypothesis in such a way as to actually prove out whether it is true or false. Depending on the circumstances, it may take many experiments before you can conclude for sure that your hypothesis if valid. In the case of our hypothesis about the temperature outside, there are a couple of experiments you could perform to test this out. Look at a thermometer on the window. In doing so, you see that it shows the temperature outside is 5 degrees. Okay, that is one indication that it is not so warm outside. It’s not necessarily conclusive evidence yet, but it’s a start. The thermometer could be off because it could be broken and also, it may only be measuring the temperature in one specific location where there could be a “cold pocket”. Open the window and stick your head outside. The freezing cold temperature assaults your face and the slight “breeze” stings your skin. You quickly close the window. You determine at this point that your experiment is over. One last point on experimentation. To find out whether it is cold outside, you could always just consult Google or the Weather Channel. But that is not really an experiment. Things on the internet or on the TV or radio come from people. When you “google” something, you are basically asking someone else for their opinion or their ideas. No matter who is telling you what, there is always a chance they could be wrong. They may be able to point you in a direction or help you with an experiment, but that is not the same thing as accepting their opinions or ideas as facts. One of the most common mistakes in logic and critical thinking is to take someone else’s opinions or “facts” as true without verifying it yourself first. 4. Analyze your data to determine whether to accept or reject the hypothesis. Now that you have the results of your experiments, you use that to determine whether your hypothesis was correct. In our simple case, we have the following results: Temperature reads 5 degrees outside. Physical test of the air and temperature indicated that it was frigid and very uncomfortable. The hypothesis that it is warm and tolerable outside has been proven false. It is, in fact, freezing and you decide that you are not going out without bundling up first. 5. If necessary, propose and test a new hypothesis. In this case, there is no need to proceed with further hypotheses as the one we came up with was proven wrong. At the same time, we concluded that bundling up would handle our aversion to the freezing weather. There are many other instances where you may make one hypothesis, test it out and it doesn’t turn out to be true and then you need to come up with another one. Let’s say you are working on fixing a broken air conditioner. You don’t know what the problem is exactly, but you see that a pipe is sticking out that doesn’t look like it should, so you experiment with putting it back in place. That seemed to be a good idea but the air conditioner still doesn’t work after you fix the pipe. So you look some more and see that it’s not plugged in. You formulate a new hypothesis that it may not be working because it needs electricity. You plug it in and, voila, it turns on and operates smoothly. Perhaps the pipe and the electricity both needed to be fixed before it would operate. The bottom line is that by observing, experimenting and re-evaluating the information and further experimenting, you were able to solve the problem. That is what the scientific method is for. Following these steps are the heart of critical thinking. Chances are, you already are doing these steps many times every single day. But by knowing these steps and going over them yourself, you can be more certain about what you are doing. You can also catch yourself if you miss a step or find yourself stuck. The solution to almost any problem you will encounter in life is to observe, analyze, experiment and re-evaluate based on what you find until you come to a solution. Practice, practice, practice using the steps of the scientific method and see what results you get. Every single discovery in our history, every leap forward in science or technology or anything else, was made using these steps.  They are the basis of all the rest of the critical thinking skills you can learn.  Learn them well and may your life and thinking never be the same again. Here are some practical exercises you can do: The next time you go into a space or room you are very familiar with, look around the room and observe it as though you had never seen it before. See if you can find at least three things about the space that you have never noticed before. Recall some example from your experience where a problem was solved using scientific method. Break down the steps so you can see what hypothesis you formed and how you tested it and then proved it to be correct. See if you can recall a time that you or someone you know came up with a hypothesis but then did not test it out before acting on it. What was the result? What could they have done as an experiment to test the hypothesis? The next time you encounter a problem in life, form a hypothesis about what the source of that problem might be. Perform some kind of test or experiment to see if your hypothesis is actually valid. Only after you have proven that the hypothesis is correct, come up with the solution. Notice to yourself what might have happened if you had not verified your hypothesis before acting. I am very interested in what results you get from these exercises. Please leave me any comments if you have any feedback on this. Share this: 5 thoughts on “using the scientific method in everyday life”. I totally agree with Chris Shelton critical thinking is really important to get along in life like science and questions can really help you. This helped me on my homework so I love this website THANK YOU!!!!!!!! Pingback:  Psych in Your Life – starboundkid Now that makes a good life orientation exercise. Pingback:  STS Exercise : The Scientific Method | Baratillo Pamphlet Leave a Reply Cancel reply This site uses Akismet to reduce spam. Learn how your comment data is processed . It’s a wonderful world — and universe — out there. Come explore with us!   Science News Explores Problems with ‘the scientific method’. Scientists rarely follow one straightforward path to understanding the natural world  Across ages and scientific fields, students are increasingly probing their world by engaging in the types of activities scientists do.   NASA/Goddard Space Flight Center/Bill Hrybyk Share this: Google Classroom By Jennifer Cutraro July 5, 2012 at 2:53 pm In Connecticut, first-graders load up toy cars with different amounts of mass, or stuff, and send them racing down ramps, rooting for their favorites to travel the farthest. In Texas, middle school students sample seawater from the Gulf of Mexico. And in Pennsylvania, kindergarten students debate what makes something a seed. Though separated by miles, age levels and scientific fields, one thing unites these students: They are all trying to make sense of the natural world by engaging in the kinds of activities that scientists do. You might have learned about or participated in such activities as part of something your teacher described as the “scientific method.” It’s a sequence of steps that take you from asking a question to arriving at a conclusion. But scientists rarely follow the steps of the scientific method as textbooks describe it. “The scientific method is a myth,” asserts Gary Garber, a physics teacher at Boston University Academy. The term “scientific method,” he explains, isn’t even something scientists themselves came up with. It was invented by historians and philosophers of science during the last century to make sense of how science works. Unfortunately, he says, the term is usually interpreted to mean there is only one, step-by-step approach to science. That’s a big misconception, Garber argues. “There isn’t one method of ‘doing science.’” In fact, he notes, there are many paths to finding out the answer to something. Which route a researcher chooses may depend on the field of science being studied. It might also depend on whether experimentation is possible, affordable — even ethical. In some instances, scientists may use computers to model, or simulate, conditions. Other times, researchers will test ideas in the real world. Sometimes they begin an experiment with no idea what may happen. They might disturb some system just to see what happens, Garber says, “because they’re experimenting with the unknown.” The practices of science But it’s not time to forget everything we thought we knew about how scientists work, says Heidi Schweingruber. She should know. She’s the deputy director of the Board on Science Education at the National Research Council, in Washington, D.C. In the future, she says, students and teachers will be encouraged to think not about the scientific method, but instead about “practices of science” — or the many ways in which scientists look for answers. Schweingruber and her colleagues recently developed a new set of national guidelines that highlight the practices central to how students should learn science. “In the past, students have largely been taught there’s one way to do science,” she says. “It’s been reduced to ‘Here are the five steps, and this is how every scientist does it.’“ But that one-size-fits-all approach doesn’t reflect how scientists in different fields actually “do” science, she says. For example, experimental physicists are scientists who study how particles such as electrons, ions and protons behave. These scientists might perform controlled experiments, starting with clearly defined initial conditions. Then they will change one variable, or factor, at a time.  For instance, experimental physicists might smash protons into various types of atoms, such as helium in one experiment, carbon during a second experiment and lead in a third. Then they would compare differences in the collisions to learn more about the building blocks of atoms. In contrast, geologists, scientists who study the history of Earth as recorded in rocks, won’t necessarily do experiments, Schweingruber points out. “They’re going into the field, looking at landforms, looking at clues and doing a reconstruction to figure out the past,” she explains. Geologists are still collecting evidence, “but it’s a different kind of evidence.” Current ways of teaching science might also give hypothesis testing more emphasis than it deserves, says Susan Singer, a biologist at Carleton College in Northfield, Minn. A hypothesis is a testable idea or explanation for something. Starting with a hypothesis is a good way to do science, she acknowledges, “but it’s not the only way.” “Often, we just start by saying, ‘I wonder’“ Singer says. “Maybe it gives rise to a hypothesis.” Other times, she says, you may need to first gather some data and look to see if a pattern emerges. Figuring out a species’ entire genetic code, for example, generates enormous collections of data. Scientists who want to make sense of these data don’t always start with a hypothesis, Singer says. “You can go in with a question,” she says. But that question might be: What environmental conditions — like temperature or pollution or moisture level — trigger certain genes to turn “on” or “off?” The upside of mistakes Scientists also recognize something that few students do: Mistakes and unexpected results can be blessings in disguise. An experiment that doesn’t give the results that a scientist expected does not necessarily mean a researcher did something wrong. In fact, mistakes often point to unexpected results — and sometimes more important data — than the findings that scientists initially anticipated. “Ninety percent of the experiments I did as a scientist didn’t work out,” says Bill Wallace, a former biologist with the National Institutes of Health. “The history of science is full of controversies and mistakes that were made,” notes Wallace, who now teaches high school science at Georgetown Day School in Washington, D.C. “But the way we teach science is: The scientist did an experiment, got a result, it got into the textbook.” There is little indication for how these discoveries came about, he says. Some might have been expected. Others might reflect what a researcher stumbled upon — either by accident (for example, a flood in the lab) or through some mistake introduced by the scientist. Schweingruber agrees. She thinks American classrooms treat mistakes too harshly. “Sometimes, seeing where you made a mistake gives you a lot more insight for learning than when you got everything right,” she says. In other words: People often learn more from mistakes than from having experiments turn out the way they expected. Practicing science at school One way teachers make science more authentic, or representative of how scientists work, is to have students do open-ended experiments. Such experiments are conducted simply to find out what happens when a variable is changed. Carmen Andrews, a science specialist at Thurgood Marshall Middle School in Bridgeport, Conn., has her first-grade students record on graphs how far toy cars travel on the floor after racing down a ramp. The distance changes depending on how much stuff — or mass —the cars carry. Andrews’ 6-year-old scientists perform simple investigations, interpret their data, use mathematics and then explain their observations. Those are four of the key practices of science highlighted in the new science-teaching guidelines. Students “quickly see that when they add more mass, their cars travel farther,” Andrews explains. They get the sense that a force pulls on the heavier cars, causing them to travel farther. Other teachers use something they call project-based learning. This is where they pose a question or identify a problem. Then they work with their students to develop a long-term class activity to investigate it. Three times a year, Lollie Garay and her middle school students at the Redd School in Houston storm onto a southern Texas beach. There, this science teacher and her class collect seawater samples to understand how human actions affect local water. Garay has also partnered with a teacher in Alaska and another in Georgia whose students take similar measurements of their coastal waters. A few times each year, these teachers arrange a videoconference between their three classrooms. This allows their students to communicate their findings — yet another key practice of science. For the students “Completing a project like this is more than ‘I did my homework,’“ Garay says. “They’re buying into this process of doing authentic research. They’re learning the process of science by doing it.” It’s a point other science educators echo. In the same way that learning a list of French words is not the same as having a conversation in French, Singer says, learning a list of scientific terms and concepts is not doing science. “Sometimes, you do just have to learn what the words mean,” Singer says. “But that’s not doing science; it’s just getting enough background info [so] that you can join in the conversation.” Even the youngest students can take part in the conversation, notes Deborah Smith, at Pennsylvania State University in State College. She teamed up with a kindergarten teacher to develop a unit about seeds. Rather than reading to the children or showing them pictures in a book, Smith and the other teacher convened a “scientific conference.” They broke the class into small groups and gave each group a collection of small items. These included seeds, pebbles and shells. Then the students were asked to explain why they thought each item was — or was not — a seed. “The kids disagreed about almost every object we showed them,” Smith says. Some argued that all seeds have to be black. Or hard. Or have a certain shape. That spontaneous discussion and debate was exactly what Smith had hoped for. “One of the things we explained early on is that scientists have all kinds of ideas and that they often disagree,” Smith says. “But they also listen to what people say, look at their evidence and think about their ideas. That’s what scientists do.” By talking and sharing ideas — and yes, sometimes arguing —people may learn things they couldn’t resolve on their own. How scientists use the practices of science Talking and sharing — or communicating ideas — recently played an important role in Singer’s own research. She tried to figure out which gene mutation caused an unusual flower type in pea plants. She and her college students weren’t having much success in the lab. Then, they traveled to Vienna, Austria, for an international conference on plants. They went to a presentation about flower mutations in Arabidopsis , a weedy plant that serves as the equivalent to a lab rat for plant scientists. And it was at this scientific presentation that Singer had her “aha” moment. “Just listening to the talk, suddenly, in my head, it clicked: That could be our mutant,” she says. It was only when she heard another team of scientists describe their results that her own studies could move ahead, she now says. If she had not gone to that foreign meeting or if those scientists had not shared their work, Singer might not have been able to make her own breakthrough, identifying the gene mutation she was looking for. Schweingruber says that showing students the practices of science can help them to better understand how science actually works — and bring some of the excitement of science into classrooms. “What scientists do is really fun, exciting and really human,” she says. “You interact with people a lot and have a chance to be creative. That can be your school experience, too.” Power words philosopher A person who studies wisdom or enlightenment. linear In a straight line. hypothesis A testable idea. variable A part of a scientific experiment that is allowed to change in order to test a hypothesis. ethical Following agreed-upon rules of conduct. gene A tiny part of a chromosome, made up of molecules of DNA. Genes play a role in determining traits such as the shape of a leaf or the color of an animal’s fur. mutation A change in a gene. control A factor in an experiment that remains unchanged. Login to your account Change password, your password must have 8 characters or more and contain 3 of the following:. a lower case character,  an upper case character,  a special character  Password Changed Successfully Your password has been changed Create a new account Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions If the address matches an existing account you will receive an email with instructions to reset your password Request Username Can't sign in? Forgot your username? 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Click the AdBlock Plus icon in the extension bar Click the blue power button Click refresh Adblock Instructions Click the AdBlock icon Click "Don't run on pages on this site" uBlock Origin Instructions Click on the uBlock Origin icon in the extension bar Click on the big, blue power button Refresh the web page uBlock Instructions Click on the uBlock icon in the extension bar Adguard Instructions Click on the Adguard icon in the extension bar Click on the toggle next to the "Protection on this website" text Brave Instructions Click on the orange lion icon to the right of the address bar Click the toggle on the top right, shifting from "Up" to "Down Adremover Instructions Click on the AdRemover icon in the extension bar Click the "Don’t run on pages on this domain" button Click "Exclude" Adblock Genesis Instructions Click on the Adblock Genesis icon in the extension bar Click on the button that says "Whitelist Website" Super Adblocker Instructions Click on the Super Adblocker icon in the extension bar Click on the "Don’t run on pages on this domain" button Click the "Exclude" button on the pop-up Ultrablock Instructions Click on the UltraBlock icon in the extension bar Click on the "Disable UltraBlock for ‘domain name here’" button Ad Aware Instructions Click on the AdAware icon in the extension bar Click on the large orange power button Ghostery Instructions Click on the Ghostery icon in the extension bar Click on the "Trust Site" button Firefox Tracking Protection Instructions Click on the shield icon on the left side of the address bar Click on the toggle that says "Enhanced Tracking protection is ON for this site" Duck Duck Go Instructions Click on the DuckDuckGo icon in the extension bar Click on the toggle next to the words "Site Privacy Protection" Privacy Badger Instructions Click on the Privacy Badger icon in the extension bar Click on the button that says "Disable Privacy Badger for this site" Disconnect Instructions Click on the Disconnect icon in the extension bar Click the button that says "Whitelist Site" Opera Instructions Click on the blue shield icon on the right side of the address bar Click the toggle next to "Ads are blocked on this site" System Upgrade on Tue, May 28th, 2024 at 2am (EDT) Solving Everyday Problems with the Scientific Method By (author):  Don K Mak ,  Angela T Mak , and  Anthony B Mak Add to favorites Download Citations Track Citations Recommend to Library Description Supplementary This book describes how one can use The Scientific Method to solve everyday problems including medical ailments, health issues, money management, traveling, shopping, cooking, household chores, etc. It illustrates how to exploit the information collected from our five senses, how to solve problems when no information is available for the present problem situation, how to increase our chances of success by redefining a problem, and how to extrapolate our capabilities by seeing a relationship among heretofore unrelated concepts. One should formulate a hypothesis as early as possible in order to have a sense of direction regarding which path to follow. Occasionally, by making wild conjectures, creative solutions can transpire. However, hypotheses need to be well-tested. Through this way, The Scientific Method can help readers solve problems in both familiar and unfamiliar situations. Containing real-life examples of how various problems are solved — for instance, how some observant patients cure their own illnesses when medical experts have failed — this book will train readers to observe what others may have missed and conceive what others may not have contemplated. With practice, they will be able to solve more problems than they could previously imagine. In this second edition, the authors have added some more theories which they hope can help in solving everyday problems. At the same time, they have updated the book by including quite a few examples which they think are interesting. Sample Chapter(s) Chapter 1: Prelude (63 KB) Preface to the Second Edition Preface to the First Edition The Scientific Method Observation Recognition Problem Situation and Problem Definition Induction and Deduction Alternative Solutions Mathematics Probable Value Bibliography FRONT MATTER Pages: i–xvi https://doi.org/10.1142/9789813145313_fmatter Claimers and Disclaimers Chapter 1: Prelude https://doi.org/10.1142/9789813145313_0001 The father put down the newspaper. It had been raining for the last two hours. The rain finally stopped, and the sky looked clear. After all this raining, the negative ions in the atmosphere would have increased, and the air would feel fresh. The father suggested the family of four should go for a stroll. There was a park just about fifteen minutes walk from their house. Chapter 2: The Scientific Method Pages: 3–18 https://doi.org/10.1142/9789813145313_0002 In the history of philosophical ideation, scientific discoveries, and engineering inventions, it has almost never happened that a single person (or a single group of people) has come up with an idea or a similar idea that no one has ever dreamed of earlier, or at the same time. This person may not be aware of the previous findings, nor someone else in another part of the world has comparable ideas, and thus – his idea may be very original, as far as he is concerned. However, history tells us that it is highly unlikely that no one has already come up with some related concepts. Chapter 3: Observation Pages: 19–56 https://doi.org/10.1142/9789813145313_0003 Observation is the first step of the Scientific Method. However, it can infiltrate the whole scientific process – from the initial perception of a phenomenon, to proposing a solution, and right down to experimentation, where observation of the results is significant. Chapter 4: Hypothesis Pages: 57–95 https://doi.org/10.1142/9789813145313_0004 In scientific discipline, a hypothesis is a set of propositions set forth to explain the occurrence of certain phenomena. In daily language, a hypothesis can be interpreted as an assumption or guess. In this book, we employ both these definitions. Within the context of the first definition, we search for an explanation of why the problem occurs to begin with. Within the context of the second definition, we look for a plausible solution to the problem. Chapter 5: Experiment Pages: 96–121 https://doi.org/10.1142/9789813145313_0005 In scientific discipline, an experiment is a test under controlled conditions to investigate the validity of a hypothesis. In everyday language, experiment can be interpreted as a testing of an idea. In this book, we employ both these definitions. Within the context of the first definition, we attempt to confirm whether an explanation of an observation is correct. Within the context of the second definition, we check whether a proposed idea for a solution is valid. Chapter 6: Recognition Pages: 122–144 https://doi.org/10.1142/9789813145313_0006 Before we can solve any problem, we need to recognize that a problem exists in the first place. That may seem obvious, but while some problems stick out like thorns in a bush, others are hidden like plants in a forest. As such, not only do we need to tune up our observational skills to see that a problem does exist; we should also sharpen our thinking to anticipate that a problem may arise. Thus, recognition can be considered to be a combination of observing and hypothesizing. Chapter 7: Problem Situation and Problem Definition Pages: 145–152 https://doi.org/10.1142/9789813145313_0007 For just about any situation, we can look at it from different perspectives. Take the example of a piece of rock, it will look different from the eyes of a landscaper, an architect, a geologist and an artist. Chapter 8: Induction and Deduction Pages: 153–164 https://doi.org/10.1142/9789813145313_0008 Once a problem has been defined, we need to find a solution. To determine which route we can take, we will have to take a look at the knowledge that we already have in hand, and we may want to search for more information when necessary. It is therefore, much more convenient if we already have an arsenal of tools that have been stored neatly and categorized in our mind. That simply means, that we should have been observing our surroundings, and preferably have come up with some general principles that can guide us in the present problem. Chapter 9: Alternative Solutions Pages: 165–193 https://doi.org/10.1142/9789813145313_0009 While there are various ways to view a problem situation, and thus define a problem differently, there are also different ways to solve a problem once it is defined. Some of the solutions may be better than others. If we have the option of not requiring to make a snap judgement, we should wait till we have come up with several plausible solutions, and then decide which one would be the best. How do we know which solution is the best? We will discuss that in the chapter on Probable Value. Generally speaking, we should train ourselves to come up with a few suggestions, and weigh the pros and cons of each resolution. This would be equivalent to coming up with different hypotheses, and judging which one would provide an optimal result. Chapter 10: Relation Pages: 194–225 https://doi.org/10.1142/9789813145313_0010 Relation is the connection and association among different objects, events, and ideas. Problem solving, quite often, is connected with the ability to see the various relations among diversified concepts. Understanding the affiliation of a mixture of notions can be considered as hypothesizing the existence of certain correlation. Chapter 11: Mathematics Pages: 226–306 https://doi.org/10.1142/9789813145313_0011 Mathematics, even some simple arithmetic, is so important in solving some of the everyday problems, that we think a whole chapter should be written on it. Chapter 12: Probable Value Pages: 307–318 https://doi.org/10.1142/9789813145313_0012 For a certain problem, we may come up with several plausible solutions. Which path should we take? Each path would only have certain chance or probability of success in resolving the problem. If each path or solution has a different reward, we can define the probable value of each path to be the multiplication of the reward by the probability. We should, most likely, choose the path that has the highest probable value. (The term “probable value” is coined by us. The idea is appropriated from the term “expected value” in Statistics. In this sense, expected value can be considered as the sum of all probable values.). Chapter 13: Epilogue Pages: 319–322 https://doi.org/10.1142/9789813145313_0013 We run into problems every day. Even when we do not encounter any problems, it does not mean that they do not exist. Sometimes, we wish we could be able to recognize them earlier. The scientific method of observation, hypothesis, and experiment can help us recognize, define, and solve our problems. BACK MATTER Pages: 323–332 https://doi.org/10.1142/9789813145313_bmatter Praise for the First Edition: “The book was fun: a clever and entertaining introduction to basic logical thinking and maths.” “This ingenious and entertaining volume should be useful to anyone in the general public interested in self-help books; undergraduate students majoring in education or behavioral psychology; and graduates and researchers interested in problem-solving, creativity, and scientific research methodology.” Related Books Tabibito (The Traveler) Time in Powers of Ten The Grant Writing and Crowdfunding Guide for Young Investigators in Science An Outline of Scientific Writing Security, Cooperation and Disarmament Enjoy Your Science Meeting! Speaking Technically The Briefest History of Time Publishing and the Advancement of Science Order and Disorder Shedding the Veil Exploring the Integrated Science Nobel and Lasker Laureates of Chinese Descent Intelligible Design A Second Genesis Handbook of Scientific Tables Solitons and Particles Selling Science Get Your ALL ACCESS Shop Pass here → Scientific Method For Kids With Examples Kids have questions about the world around them every day, and there is so much to learn through experimentation with simple materials. You can begin using the scientific method with elementary kids. Below we’ll share with you how and when to introduce the scientific method, the steps of the scientific method, and some easy scientific method experiments. There are so many great ways to enjoy science projects with kids! What Is The Scientific Method? The scientific method is a process or method of research. A problem is identified, information about the problem is gathered, a hypothesis or question is formulated from the information, and the hypothesis is put to the test with an experiment to prove or disprove its validity. Sounds heavy… What in the world does that mean?!? It means you don’t need to try and solve the world’s biggest science questions! The scientific method is all about studying and learning things right around you. As children develop practices that involve creating, gathering data evaluating, analyzing, and communicating, they can apply these critical thinking skills to any situation. Note: The use of the best Science and Engineering Practices is also relevant to the topic of using the scientific method. Read more here and see if it fits your science planning needs. Can Young Kids Use the Scientific Method? Kids are great scientists at any age, and can use the scientific method in context to what they are learning. It can be adapted for any age! The scientific method is a valuable tool for introducing kids to a logical way to solve scientific problems. Scientists use the scientific method to study, learn, and come up with an answer! The scientific method is a process that helps double-check that answers are correct and the correct results are obtained through careful planning. Sometimes the guesses and questions change as you run your experiments. Kids can use the scientific method too on questions that are relevant to them! Let’s break the scientific method for kids down into six parts, and you can quickly see how each can be incorporated into your next science experiment. What Are The Steps In The Scientific Method? Make initial observations. Come up with a question of interest that is based on the observations. Develop a hypothesis or prediction to go along with the question. Experiment and test. Gather and record results of tests and experiments and draw conclusions. Share and discuss results. Whoa… Wait A  Minute! That sounds like a lot for a young kid! You are correct. Depending on your kid’s abilities, following all the scientific method steps precisely will not go well. Someone will get frustrated, bored, and turned off by just how cool science can be. We do not want that to happen! Using The Scientific Method For Preschool and Kindergarten Use the scientific method steps as a guideline in the back of your mind. You can cover most of the steps by talking with your kids about… What do they think will happen? What is happening ? What happened compared to what they thought would happen ? No writing is required! It’s also best to pick pretty straightforward ideas that aren’t overly involved or complicated to set up and test. Kids always have burning questions and “what ifs.” See if you can tackle their next “what if” using the scientific method by listening carefully to their conversations. You can even have them keep a journal with their “what if” questions for your next science time. Learn more about Science Activities For Preschoolers and Kindergarten Science Experiments . Now on to how to apply the scientific method for elementary kiddos and beyond. Scientific Method Steps In Action Learn more about the steps of the scientific method below, which are great for science at home with your kids or in the classroom! We have also included some simple scientific method experiments for you to enjoy. Ice Science Experiments are perfect for this! Try these 3 today ! STEP 1: Make Observations Tons of everyday activities would make for cool science experiments using the scientific method. Listen to what your kids talk about and see happening. My son noticed that ice melted pretty fast in his water. Observation is simply noticing what’s happening through our senses or with tools like a magnifying glass. Observation is used to collect and record data, enabling scientists to construct and test hypotheses and theories. Learn more about observations in science. STEP 2: Come Up With A Question  Your kids’ observations should lead to some sort of question. For my son and his ice observations, he came up with questions. Does ice melt faster in different liquids? His curiosity about what happens to the ice in liquids is a simple science experiment perfect for using the scientific method. Next! Do some research and come up with ideas! STEP 3: Develop A Prediction or Hypothesis You have made your observations, you have your question, and now you need to make a prediction about what you think will happen. A prediction is a guess at what might happen in an experiment based on observation or other information. A hypothesis is not simply a guess! It’s a statement of what you believe will happen based on the information you have gathered. My son hypothesizes that ice will melt faster in juice than in water. STEP 4: Conduct An Experiment We made a prediction that ice will melt faster in juice than it will in water, and now we have to test our hypothesis. We set up an experiment with a glass of juice, a glass of water, and an ice cube for each. For the best experiments, only one thing should change! All the things that can be changed in a science experiment are called variables. There are three types of variables; independent, dependent, and controlled. The independent variable is the one that is changed in the experiment and will affect the dependent variable. Here we will use different types of liquids to melt our ice cube in. The dependent variable is the factor that is observed or measured in the experiment. This will be the melting of the ice cubes. Set up a stopwatch or set a time limit to observe the changes! The controlled variable stays constant in the experiment. The liquids should be roughly the same temperature (as close as possible) for our ice melting experiment and measured to the same amount. So we left them out to come to room temperature. They could also be tested right out of the fridge! You can find simple science experiments here with dependent and controlled variables. STEP 5: Record Results and Draw Conclusions Make sure to record what is happening as well as the results—note changes at specific time intervals or after one set time interval. For example… Record when each ice cube is completely melted. Add drawings if you wish of the setup up and the end results. Was your prediction accurate? If it was inaccurate, record why. Write out a final conclusion to your experiment. STEP 6: Communicate Your Results This is the opportunity to talk about your hypothesis, experiment, results, and conclusion! ALTERNATIVE IDEAS: Switch out an ice cube for a lollipop or change the liquids using vinegar and cooking oil. Now you have gone through the steps of the scientific method, read on for more fun scientific method experiments to try! Free printable scientific method worksheets! Fun Scientific Method Experiments Sink or float experiment. A Sink or Float experiment is great for practicing the steps of the scientific method with younger kids. Grab this FREE printable sink or float experiment Here are a few of our favorite scientific method experiments, which are great for elementary-age kids . Of course, you can find tons more awesome and doable science projects for kids here! Magic Milk Experiment Start with demonstrating this delightful magic milk experiment. Then get kids to apply the steps of the scientific method by coming up with a question to investigate. What happens when you change the type of milk used? What Dissolves In Water Investigate  what solids dissolve in water  and what do not. Here’s a super fun science experiment for kids that’s very easy to set up! Learn about solutions, solutes, and solvents through experimenting with water and common kitchen ingredients. Apple Browning Experiment Investigate how to keep apples from turning brown with this apple oxidation experiment . What can you add to cut apples to stop or slow the oxidation process? Freezing Water Experiment Will it freeze? What happens to the freezing point of water when you add salt? Viscosity Experiment Learn about the viscosity of fluids with a simple  viscosity experiment . Grab some marbles and add them to different household liquids to find out which one will fall to the bottom first.  Seed Germination Experiment Set up a simple seed germination experiment . Catapult Experiment Make a simple popsicle stick catapult and use one of our experiment ideas to investigate from rubber band tension to changes in launch angle and more. How far can you fling your objects? Take measurements and find out. Floating Orange Investigate whether an orange floats or sinks in water, and what happens if you use different types of oranges. Learn about buoyancy and density with a simple ingredient from the kitchen, an orange. Bread Mold Experiment Grow mold on bread for science, and investigate how factors such as moisture, temperature, and air affect mold growth.  Eggshell Strength Experiment Test how strong an egg is with this eggshell strength experiment . Grab some eggs, and find out how much weight an egg can support. Free Printable Science Fair Starter Guide Are you looking to plan a science fair project, make a science fair board, or want an easy guide to set up science experiments? Learn more about prepping for a science fair and grab this free printable science fair project pack here! If you want a variety of science fair experiments with instructions, make sure to pick up a copy of our Science Project Pack in the shop. Bonus STEM Projects For Kids STEM activities include science, technology, engineering, and mathematics. As well as our kids science experiments, we have lots of fun STEM activities for you to try. Check out these STEM ideas below… Building Activities Engineering Projects For Kids What Is Engineering For Kids? LEGO Engineering Projects Coding Activities For Kids STEM Worksheets Top 10 STEM Challenges For Kids Printable Science Projects Pack If you’re looking to grab all of our printable science projects in one convenient place plus exclusive worksheets and bonuses like a STEAM Project pack, our Science Project Pack is what you need! Over 300+ Pages! 90+ classic science activities  with journal pages, supply lists, set up and process, and science information.  NEW! Activity-specific observation pages! Best science practices posters  and our original science method process folders for extra alternatives! Be a Collector activities pack  introduces kids to the world of making collections through the eyes of a scientist. What will they collect first? Know the Words Science vocabulary pack  includes flashcards, crosswords, and word searches that illuminate keywords in the experiments! My science journal writing prompts  explore what it means to be a scientist!! Bonus STEAM Project Pack:  Art meets science with doable projects! Bonus Quick Grab Packs for Biology, Earth Science, Chemistry, and Physics 19 Comments A great post and sure to help extend children’s thinking! I would like to download the 6 steps but the blue download button doesn’t seem to be working for me. Thank you! All fixed. You should be able to download now! Pingback: Popsicle Stick Catapult Ideas for Kids STEM Activity Pingback: Magical Dancing Corn Thanksgiving Science Experiment Pingback: Shadow Science Physics Activity With Animal Puppets (FREE Printable) Pingback: Books to inspire your young scientists! – Mom Read It Pingback: Seed Jar Science Experiment for Spring STEM Activities with Kids Pingback: Magic Milk Classic Science Experiment Kids Science Pingback: Earth Day Science Activity and Homemade Liquid Density Lava Lamp Pingback: Dissolving Candy Hearts Science Experiment for Valentine's Day Pingback: Seashells With Vinegar Ocean Experiment | Little Bins for Little Hands Pingback: DIY Snow Globe For Kids | Little Bins for Little Hands Pingback: Science Project Ideas with Usable Tips From a Teacher! Pingback: Drops Of Water On A Penny | Little Bins for Little Hands Pingback: The BEST Very Simple Science Experiments for Kids to Try Anywhere it is so great, thanks a lot. This helped for a science project.Thanks so much. Comments are closed. Subscribe to receive a free 5-Day STEM Challenge Guide ~ projects to try now ~. 10 Hard Math Problems That Continue to Stump Even the Brightest Minds Maybe you’ll have better luck. For now, you can take a crack at the hardest math problems known to man, woman, and machine. For more puzzles and brainteasers, check out Puzzmo . ✅ More from Popular Mechanics : To Create His Geometric Artwork, M.C. Escher Had to Learn Math the Hard Way Fourier Transforms: The Math That Made Color TV Possible The Game of Trees is a Mad Math Theory That Is Impossible to Prove The Collatz Conjecture In September 2019, news broke regarding progress on this 82-year-old question, thanks to prolific mathematician Terence Tao. And while the story of Tao’s breakthrough is promising, the problem isn’t fully solved yet. A refresher on the Collatz Conjecture : It’s all about that function f(n), shown above, which takes even numbers and cuts them in half, while odd numbers get tripled and then added to 1. Take any natural number, apply f, then apply f again and again. You eventually land on 1, for every number we’ve ever checked. The Conjecture is that this is true for all natural numbers (positive integers from 1 through infinity). ✅ Down the Rabbit Hole: The Math That Helps the James Webb Space Telescope Sit Steady in Space Tao’s recent work is a near-solution to the Collatz Conjecture in some subtle ways. But he most likely can’t adapt his methods to yield a complete solution to the problem, as Tao subsequently explained. So, we might be working on it for decades longer. The Conjecture lives in the math discipline known as Dynamical Systems , or the study of situations that change over time in semi-predictable ways. It looks like a simple, innocuous question, but that’s what makes it special. Why is such a basic question so hard to answer? It serves as a benchmark for our understanding; once we solve it, then we can proceed onto much more complicated matters. The study of dynamical systems could become more robust than anyone today could imagine. But we’ll need to solve the Collatz Conjecture for the subject to flourish. Goldbach’s Conjecture One of the greatest unsolved mysteries in math is also very easy to write. Goldbach’s Conjecture is, “Every even number (greater than two) is the sum of two primes.” You check this in your head for small numbers: 18 is 13+5, and 42 is 23+19. Computers have checked the Conjecture for numbers up to some magnitude. But we need proof for all natural numbers. Goldbach’s Conjecture precipitated from letters in 1742 between German mathematician Christian Goldbach and legendary Swiss mathematician Leonhard Euler , considered one of the greatest in math history. As Euler put it, “I regard [it] as a completely certain theorem, although I cannot prove it.” ✅ Dive In: The Math Behind Our Current Theory of Human Color Perception Is Wrong Euler may have sensed what makes this problem counterintuitively hard to solve. When you look at larger numbers, they have more ways of being written as sums of primes, not less. Like how 3+5 is the only way to break 8 into two primes, but 42 can broken into 5+37, 11+31, 13+29, and 19+23. So it feels like Goldbach’s Conjecture is an understatement for very large numbers. Still, a proof of the conjecture for all numbers eludes mathematicians to this day. It stands as one of the oldest open questions in all of math. The Twin Prime Conjecture Together with Goldbach’s, the Twin Prime Conjecture is the most famous in Number Theory—or the study of natural numbers and their properties, frequently involving prime numbers. Since you've known these numbers since grade school, stating the conjectures is easy. When two primes have a difference of 2, they’re called twin primes. So 11 and 13 are twin primes, as are 599 and 601. Now, it's a Day 1 Number Theory fact that there are infinitely many prime numbers. So, are there infinitely many twin primes? The Twin Prime Conjecture says yes. Let’s go a bit deeper. The first in a pair of twin primes is, with one exception, always 1 less than a multiple of 6. And so the second twin prime is always 1 more than a multiple of 6. You can understand why, if you’re ready to follow a bit of heady Number Theory. ✅ Keep Learning: If We Draw Graphs Like This, We Can Change Computers Forever All primes after 2 are odd. Even numbers are always 0, 2, or 4 more than a multiple of 6, while odd numbers are always 1, 3, or 5 more than a multiple of 6. Well, one of those three possibilities for odd numbers causes an issue. If a number is 3 more than a multiple of 6, then it has a factor of 3. Having a factor of 3 means a number isn’t prime (with the sole exception of 3 itself). And that's why every third odd number can't be prime. How’s your head after that paragraph? Now imagine the headaches of everyone who has tried to solve this problem in the last 170 years. The good news is that we’ve made some promising progress in the last decade. Mathematicians have managed to tackle closer and closer versions of the Twin Prime Conjecture. This was their idea: Trouble proving there are infinitely many primes with a difference of 2? How about proving there are infinitely many primes with a difference of 70,000,000? That was cleverly proven in 2013 by Yitang Zhang at the University of New Hampshire. For the last six years, mathematicians have been improving that number in Zhang’s proof, from millions down to hundreds. Taking it down all the way to 2 will be the solution to the Twin Prime Conjecture. The closest we’ve come —given some subtle technical assumptions—is 6. Time will tell if the last step from 6 to 2 is right around the corner, or if that last part will challenge mathematicians for decades longer. The Riemann Hypothesis Today’s mathematicians would probably agree that the Riemann Hypothesis is the most significant open problem in all of math. It’s one of the seven Millennium Prize Problems , with $1 million reward for its solution. It has implications deep into various branches of math, but it’s also simple enough that we can explain the basic idea right here. There is a function, called the Riemann zeta function, written in the image above. For each s, this function gives an infinite sum, which takes some basic calculus to approach for even the simplest values of s. For example, if s=2, then 𝜁(s) is the well-known series 1 + 1/4 + 1/9 + 1/16 + …, which strangely adds up to exactly 𝜋²/6. When s is a complex number—one that looks like a+b𝑖, using the imaginary number 𝑖—finding 𝜁(s) gets tricky. So tricky, in fact, that it’s become the ultimate math question. Specifically, the Riemann Hypothesis is about when 𝜁(s)=0; the official statement is, “Every nontrivial zero of the Riemann zeta function has real part 1/2.” On the plane of complex numbers, this means the function has a certain behavior along a special vertical line. The hypothesis is that the behavior continues along that line infinitely. ✅ Stay Curious: How to Paint a Room Using Math The Hypothesis and the zeta function come from German mathematician Bernhard Riemann, who described them in 1859. Riemann developed them while studying prime numbers and their distribution. Our understanding of prime numbers has flourished in the 160 years since, and Riemann would never have imagined the power of supercomputers. But lacking a solution to the Riemann Hypothesis is a major setback. If the Riemann Hypothesis were solved tomorrow, it would unlock an avalanche of further progress. It would be huge news throughout the subjects of Number Theory and Analysis. Until then, the Riemann Hypothesis remains one of the largest dams to the river of math research. The Birch and Swinnerton-Dyer Conjecture The Birch and Swinnerton-Dyer Conjecture is another of the six unsolved Millennium Prize Problems, and it’s the only other one we can remotely describe in plain English. This Conjecture involves the math topic known as Elliptic Curves. When we recently wrote about the toughest math problems that have been solved , we mentioned one of the greatest achievements in 20th-century math: the solution to Fermat’s Last Theorem. Sir Andrew Wiles solved it using Elliptic Curves. So, you could call this a very powerful new branch of math. ✅ The Latest: Mathematicians Discovered Something Mind-Blowing About the Number 15 In a nutshell, an elliptic curve is a special kind of function. They take the unthreatening-looking form y²=x³+ax+b. It turns out functions like this have certain properties that cast insight into math topics like Algebra and Number Theory. British mathematicians Bryan Birch and Peter Swinnerton-Dyer developed their conjecture in the 1960s. Its exact statement is very technical, and has evolved over the years. One of the main stewards of this evolution has been none other than Wiles. To see its current status and complexity, check out this famous update by Wells in 2006. The Kissing Number Problem A broad category of problems in math are called the Sphere Packing Problems. They range from pure math to practical applications, generally putting math terminology to the idea of stacking many spheres in a given space, like fruit at the grocery store. Some questions in this study have full solutions, while some simple ones leave us stumped, like the Kissing Number Problem. When a bunch of spheres are packed in some region, each sphere has a Kissing Number, which is the number of other spheres it’s touching; if you’re touching 6 neighboring spheres, then your kissing number is 6. Nothing tricky. A packed bunch of spheres will have an average kissing number, which helps mathematically describe the situation. But a basic question about the kissing number stands unanswered. ✅ Miracles Happen: Mathematicians Finally Make a Breakthrough on the Ramsey Number First, a note on dimensions. Dimensions have a specific meaning in math: they’re independent coordinate axes. The x-axis and y-axis show the two dimensions of a coordinate plane. When a character in a sci-fi show says they’re going to a different dimension, that doesn’t make mathematical sense. You can’t go to the x-axis. A 1-dimensional thing is a line, and 2-dimensional thing is a plane. For these low numbers, mathematicians have proven the maximum possible kissing number for spheres of that many dimensions. It’s 2 when you’re on a 1-D line—one sphere to your left and the other to your right. There’s proof of an exact number for 3 dimensions, although that took until the 1950s. Beyond 3 dimensions, the Kissing Problem is mostly unsolved. Mathematicians have slowly whittled the possibilities to fairly narrow ranges for up to 24 dimensions, with a few exactly known, as you can see on this chart . For larger numbers, or a general form, the problem is wide open. There are several hurdles to a full solution, including computational limitations. So expect incremental progress on this problem for years to come. The Unknotting Problem The simplest version of the Unknotting Problem has been solved, so there’s already some success with this story. Solving the full version of the problem will be an even bigger triumph. You probably haven’t heard of the math subject Knot Theory . It ’s taught in virtually no high schools, and few colleges. The idea is to try and apply formal math ideas, like proofs, to knots, like … well, what you tie your shoes with. For example, you might know how to tie a “square knot” and a “granny knot.” They have the same steps except that one twist is reversed from the square knot to the granny knot. But can you prove that those knots are different? Well, knot theorists can. ✅ Up Next: The Amazing Math Inside the Rubik’s Cube Knot theorists’ holy grail problem was an algorithm to identify if some tangled mess is truly knotted, or if it can be disentangled to nothing. The cool news is that this has been accomplished! Several computer algorithms for this have been written in the last 20 years, and some of them even animate the process . But the Unknotting Problem remains computational. In technical terms, it’s known that the Unknotting Problem is in NP, while we don ’ t know if it’s in P. That roughly means that we know our algorithms are capable of unknotting knots of any complexity, but that as they get more complicated, it starts to take an impossibly long time. For now. If someone comes up with an algorithm that can unknot any knot in what’s called polynomial time, that will put the Unknotting Problem fully to rest. On the flip side, someone could prove that isn’t possible, and that the Unknotting Problem’s computational intensity is unavoidably profound. Eventually, we’ll find out. The Large Cardinal Project If you’ve never heard of Large Cardinals , get ready to learn. In the late 19th century, a German mathematician named Georg Cantor figured out that infinity comes in different sizes. Some infinite sets truly have more elements than others in a deep mathematical way, and Cantor proved it. There is the first infinite size, the smallest infinity , which gets denoted ℵ₀. That’s a Hebrew letter aleph; it reads as “aleph-zero.” It’s the size of the set of natural numbers, so that gets written |ℕ|=ℵ₀. Next, some common sets are larger than size ℵ₀. The major example Cantor proved is that the set of real numbers is bigger, written |ℝ|>ℵ₀. But the reals aren’t that big; we’re just getting started on the infinite sizes. ✅ More Mind-Blowing Stuff: Mathematicians Discovered a New 13-Sided Shape That Can Do Remarkable Things For the really big stuff, mathematicians keep discovering larger and larger sizes, or what we call Large Cardinals. It’s a process of pure math that goes like this: Someone says, “I thought of a definition for a cardinal, and I can prove this cardinal is bigger than all the known cardinals.” Then, if their proof is good, that’s the new largest known cardinal. Until someone else comes up with a larger one. Throughout the 20th century, the frontier of known large cardinals was steadily pushed forward. There’s now even a beautiful wiki of known large cardinals , named in honor of Cantor. So, will this ever end? The answer is broadly yes, although it gets very complicated. In some senses, the top of the large cardinal hierarchy is in sight. Some theorems have been proven, which impose a sort of ceiling on the possibilities for large cardinals. But many open questions remain, and new cardinals have been nailed down as recently as 2019. It’s very possible we will be discovering more for decades to come. Hopefully we’ll eventually have a comprehensive list of all large cardinals. What’s the Deal with 𝜋+e? Given everything we know about two of math’s most famous constants, 𝜋 and e , it’s a bit surprising how lost we are when they’re added together. This mystery is all about algebraic real numbers . The definition: A real number is algebraic if it’s the root of some polynomial with integer coefficients. For example, x²-6 is a polynomial with integer coefficients, since 1 and -6 are integers. The roots of x²-6=0 are x=√6 and x=-√6, so that means √6 and -√6 are algebraic numbers. ✅ Try It Yourself: Can You Solve This Viral Brain Teaser From TikTok? All rational numbers, and roots of rational numbers, are algebraic. So it might feel like “most” real numbers are algebraic. Turns out, it’s actually the opposite. The antonym to algebraic is transcendental, and it turns out almost all real numbers are transcendental—for certain mathematical meanings of “almost all.” So who’s algebraic , and who’s transcendental? The real number 𝜋 goes back to ancient math, while the number e has been around since the 17th century. You’ve probably heard of both, and you’d think we know the answer to every basic question to be asked about them, right? Well, we do know that both 𝜋 and e are transcendental. But somehow it’s unknown whether 𝜋+e is algebraic or transcendental. Similarly, we don’t know about 𝜋e, 𝜋/e, and other simple combinations of them. So there are incredibly basic questions about numbers we’ve known for millennia that still remain mysterious. Is 𝛾 Rational? Here’s another problem that’s very easy to write, but hard to solve. All you need to recall is the definition of rational numbers. Rational numbers can be written in the form p/q, where p and q are integers. So, 42 and -11/3 are rational, while 𝜋 and √2 are not. It’s a very basic property, so you’d think we can easily tell when a number is rational or not, right? Meet the Euler-Mascheroni constant 𝛾, which is a lowercase Greek gamma. It’s a real number, approximately 0.5772, with a closed form that’s not terribly ugly; it looks like the image above. ✅ One More Thing: Teens Have Proven the Pythagorean Theorem With Trigonometry. That Should Be Impossible The sleek way of putting words to those symbols is “gamma is the limit of the difference of the harmonic series and the natural log.” So, it’s a combination of two very well-understood mathematical objects. It has other neat closed forms, and appears in hundreds of formulas. But somehow, we don’t even know if 𝛾 is rational. We’ve calculated it to half a trillion digits, yet nobody can prove if it’s rational or not. The popular prediction is that 𝛾 is irrational. Along with our previous example 𝜋+e, we have another question of a simple property for a well-known number, and we can’t even answer it. Dave Linkletter is a Ph.D. candidate in Pure Mathematics at the University of Nevada, Las Vegas. His research is in Large Cardinal Set Theory. He also teaches undergrad classes, and enjoys breaking down popular math topics for wide audiences. .css-cuqpxl:before{padding-right:0.3125rem;content:'//';display:inline;} Pop Mech Pro .css-xtujxj:before{padding-left:0.3125rem;content:'//';display:inline;} How to Live Forever, or Die Trying The Army & Navy Working Together Defense Missiles How Russia Copied America’s Deadliest Missile North Korea Sends “Poop Balloons” Into South Korea Plane Flown by 'Ace of Aces' Pilot Finally Found The F-35 Is Still One of the Safest Planes The Air Force’s Upcoming “Doomsday Plane” Replacem Meet the Marines' New Kamikaze Drone Did Russia Launch a Weapon Near a U.S. Satellite? A Groundbreaking Discovery For Interstellar Travel America's Missile Defense Has Entered a New Era Appointments at Mayo Clinic Stress management Chronic stress puts your health at risk Chronic stress can wreak havoc on your mind and body. Take steps to control your stress. Your body is made to react to stress in ways meant to protect you against threats from predators and other aggressors. Such threats are rare today. But that doesn't mean that life is free of stress. Instead, you likely face many demands each day. For example, you may take on a huge workload, pay bills or take care of your family. Your body treats these everyday tasks as threats. Because of this, you may feel as if you're always under attack. But you can fight back. You don't have to let stress control your life. Understanding the natural stress response When you face a perceived threat, a tiny region at the brain's base, called the hypothalamus, sets off an alarm system in the body. An example of a perceived threat is a large dog barking at you during your morning walk. Through nerve and hormonal signals, this system prompts the adrenal glands, found atop the kidneys, to release a surge of hormones, such as adrenaline and cortisol. Adrenaline makes the heart beat faster, causes blood pressure to go up and gives you more energy. Cortisol, the primary stress hormone, increases sugar, also called glucose, in the bloodstream, enhances the brain's use of glucose and increases the availability of substances in the body that repair tissues. Cortisol also slows functions that would be nonessential or harmful in a fight-or-flight situation. It changes immune system responses and suppresses the digestive system, the reproductive system and growth processes. This complex natural alarm system also communicates with the brain regions that control mood, motivation and fear. When the natural stress response goes wild The body's stress response system is usually self-limiting. Once a perceived threat has passed, hormones return to typical levels. As adrenaline and cortisol levels drop, your heart rate and blood pressure return to typical levels. Other systems go back to their regular activities. But when stressors are always present and you always feel under attack, that fight-or-flight reaction stays turned on. The long-term activation of the stress response system and too much exposure to cortisol and other stress hormones can disrupt almost all the body's processes. This puts you at higher risk of many health problems, including: Depression. Digestive problems. Muscle tension and pain. Heart disease, heart attack, high blood pressure and stroke. Sleep problems. Weight gain. Problems with memory and focus. That's why it's so important to learn healthy ways to cope with your life stressors. Why you react to life stressors the way you do Your reaction to a potentially stressful event is different from everyone else's. How you react to your life stressors is affected by such factors as: Genetics. The genes that control the stress response keep most people at a fairly steady emotional level, only sometimes priming the body for fight or flight. More active or less active stress responses may stem from slight differences in these genes. Life experiences. Strong stress reactions sometimes can be traced to traumatic events. People who were neglected or abused as children tend to be especially at risk of experiencing high stress. The same is true of airplane crash survivors, people in the military, police officers and firefighters, and people who have experienced violent crime. You may have some friends who seem relaxed about almost everything. And you may have other friends who react strongly to the slightest stress. Most people react to life stressors somewhere between those extremes. Learning to react to stress in a healthy way Stressful events are facts of life. And you may not be able to change your current situation. But you can take steps to manage the impact these events have on you. You can learn to identify what causes you stress. And you can learn how to take care of yourself physically and emotionally in the face of stressful situations. Try these stress management tips: Eat a healthy diet and get regular exercise. Get plenty of sleep too. Do relaxation exercises such as yoga, deep breathing, massage or meditation. Keep a journal. Write about your thoughts or what you're grateful for in your life. Take time for hobbies, such as reading or listening to music. Or watch your favorite show or movie. Foster healthy friendships and talk with friends and family. Have a sense of humor. Find ways to include humor and laughter in your life, such as watching funny movies or looking at joke websites. Volunteer in your community. Organize and focus on what you need to get done at home and work and remove tasks that aren't needed. Seek professional counseling. A counselor can help you learn specific coping skills to manage stress. Stay away from unhealthy ways of managing your stress, such as using alcohol, tobacco, drugs or excess food. If you're worried that your use of these products has gone up or changed due to stress, talk to your health care provider. There are many rewards for learning to manage stress. For example, you can have peace of mind, fewer stressors and less anxiety, a better quality of life, improvement in conditions such as high blood pressure, better self-control and focus, and better relationships. And it might even lead to a longer, healthier life. There is a problem with information submitted for this request. Review/update the information highlighted below and resubmit the form. From Mayo Clinic to your inbox Sign up for free and stay up to date on research advancements, health tips, current health topics, and expertise on managing health. Click here for an email preview. Error Email field is required Error Include a valid email address To provide you with the most relevant and helpful information, and understand which information is beneficial, we may combine your email and website usage information with other information we have about you. If you are a Mayo Clinic patient, this could include protected health information. If we combine this information with your protected health information, we will treat all of that information as protected health information and will only use or disclose that information as set forth in our notice of privacy practices. You may opt-out of email communications at any time by clicking on the unsubscribe link in the e-mail. Thank you for subscribing! You'll soon start receiving the latest Mayo Clinic health information you requested in your inbox. Sorry something went wrong with your subscription Please, try again in a couple of minutes How stress affects your health. American Psychological Association. https://www.apa.org/topics/stress/health. Accessed March 19, 2021. Stress effects on the body. American Psychological Association. https://www.apa.org/topics/stress/body. Accessed March 19, 2021. Lower stress: How does stress affect the body? American Heart Association. https://www.heart.org/en/healthy-living/healthy-lifestyle/stress-management/lower-stress-how-does-stress-affect-the-body. Accessed March 18, 2021. Stress and your health. U.S. Department of Health & Human Services. https://www.womenshealth.gov/mental-health/good-mental-health/stress-and-your-health. Accessed March 18, 2021. AskMayoExpert. Stress management and resiliency (adult). Mayo Clinic. 2019. Seaward BL. Essentials of Managing Stress. 5th ed. Jones & Bartlett Learning; 2021. Seaward BL. Managing Stress: Skills for Self-Care, Personal Resiliency and Work-Life Balance in a Rapidly Changing World. 10th ed. Jones & Bartlett Learning; 2022. Olpin M, et al. 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It's easier to do than you think. Certified Sleep Science Coach, Certified Stress Management Coach If your better half is keeping you awake at night, you aren't alone --  1 in 3 Americans report that their partner negatively affects their sleep. No matter how much we love them, sometimes they're the reason we can't get any shut-eye. Whether it's snoring or blanket-stealing, incompatible sleep patterns greatly affect the quality of your sleep.  If you're at your breaking point but aren't ready to commit to a  sleep divorce , the Scandinavian sleeping method may drastically improve how you sleep at night. I'll tell you what the Scandinavian sleep method is, why it works and how to start using it to improve your sleep. Also, don't miss  our editor's favorite sleep tips , how to tackle anxiety before bed  and whether tech can help you sleep better .  What is the Scandinavian sleeping method? The Scandinavian sleeping method is common in some parts of the world — Sweden, Norway, Denmark and some other parts of  Europe. The idea is simple: Instead of sharing a blanket at night, you and your partner each have your own. It's not about avoiding intimacy or sacrificing a part of your relationship. It's about prioritizing your sleep needs so that both of you can wake up well-rested and energized.  Most people use two twin-size comforters or duvets for the Scandinavian sleeping method. This sleeping style typically works best on king mattresses to give the separate blankets the most room, but  queen mattresses work fine for most people.  Traditionally, you forgo the shared flat sheet for this. If you're like me and love flat sheets , you can always opt for two flat sheets, in addition to separate blankets. There's no right or wrong way to do it. Read more: Best Duvet Covers for Your Bed Two comforters can help you sleep better Sharing a comforter with your partner might not be the best option for your needs, and that's OK. Sleep is inherently a single-player sport. It's not something you are required to share with your partner. For many people, sharing a blanket might not be the best move for your sleep quality. One study found that sharing comforters results in 30% more interrupted sleep .  By each having their own blanket, the half-asleep tug-of-war battle is eliminated, and so are all the times you wake up because you're cold and blanketless. You also can adjust positions at night without worrying about affecting your partner.  Remember that the Scandinavian sleeping method isn't reserved just for those who live with a blanket hogger. It's a good option for anyone who tosses and turns or has a different sleeping pattern that may wake up their partner.  Comforters vs. duvets Comforters and duvets are fluffy blankets that come in various thicknesses and materials for temperature regulation. A comforter is one complete piece, while a duvet is meant to be inserted into a cover or coverlet. Duvet covers are interchangeable, so you can easily alter the look of your bed without buying a whole new comforter set. Duvets are also easier to clean because you can remove and wash the cover. Comforters are easier to use because they're one blanket with no cover. They're usually quilted or stitched so that the material inside is secure and evenly distributed. You won't have "bunching up" issues with comforters like you might with a duvet in its cover.  Which one should you use? For the Scandinavian sleeping method, both duvets and comforters work great as long as each partner uses their own. If I had to choose between the two options, I would recommend comforters for their simplicity. Using two duvets means you'll have double the work of reinserting them into their respective covers every time you wash the bedding, which can be awkward and time-consuming. Ultimately, it's up to your preferences and whatever will help you and your partner sleep best. You can personalize your sleep experience  When my boyfriend is asleep, he turns into an (almost literal) pool of lava, kicking off the blanket to cool down. I'm not like that; I like to burrow into my blanket all night.  Having two blankets allows for personalization in temperature. Temperature is essential when we sleep; it triggers when we fall asleep and wake up . Getting too warm or too cold will interrupt our circadian rhythm . If your partner is a hot sleeper who only wants to use a sheet while you like to wrap in a comforter burrito , then you have that freedom with separate bedding. You have the choice to use a quilt, fuzzy blanket or light duvet, while your partner could use nothing at all — or something more substantial, like a weighted blanket . Will two blankets solve all of your problems? If your sleep problems are due to your or your partner's underlying sleep disorder, using two blankets won't solve everything, although it can help protect you from additional sleep disturbances. Sleep is essential for health. When we sleep, our bodies go into recharge mode. Getting enough sleep will result in better memory and concentration, a stronger immune system and better heart health. If you're not getting enough sleep at night , it's important to figure out why.  Read more: Best Mattresses for Good Sleep It may be as simple as using the wrong pillow or sleeping on a mattress that's too old and needs to be replaced. It could be something more serious like sleep apnea or insomnia that can significantly disturb your sleep. It's best to talk to your doctor if you're not sleeping well to explore the underlying causes. 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The scientific method has five basic steps, plus one feedback step: Make an observation. Ask a question. Form a hypothesis, or testable explanation. Make a prediction based on the hypothesis. Test the prediction. What is the Scientific Method: How does it work and why is it important Article. Research Process. The scientific method is a systematic process involving steps like defining questions, forming hypotheses, conducting experiments, and analyzing data. It minimizes biases and enables replicable research, leading to groundbreaking discoveries like Einstein's theory of relativity, penicillin, and the structure of DNA. A Guide to Using the Scientific Method in Everyday Life A brief history of the scientific method. The scientific method has its roots in the sixteenth and seventeenth centuries. Philosophers Francis Bacon and René Descartes are often credited with formalizing the scientific method because they contrasted the idea that research should be guided by metaphysical pre-conceived concepts of the nature of reality—a position that, at the time, was ... The 6 Scientific Method Steps and How to Use Them One of the most important pieces to the scientific method is skepticism —the goal is to find truth, not to confirm a particular thought. That requires reevaluation and repeated experimentation, as well as examining your thinking through rigorous study. There are in fact multiple scientific methods, as the basic structure can be easily modified. 1.2: Scientific Approach for Solving Problems In doing so, they are using the scientific method. 1.2: Scientific Approach for Solving Problems is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts. Chemists expand their knowledge by making observations, carrying out experiments, and testing hypotheses to develop laws to summarize their results and ... The Scientific Method: What Is It? The scientific method is useful whenever you need to reason logically about your questions and gather evidence to support your problem-solving efforts. So, you can use it in everyday life to ... Scientific method The scientific method is an empirical method for acquiring knowledge that has characterized the development of science since at least the 17th century. The scientific method involves careful observation coupled with rigorous scepticism, because cognitive assumptions can distort the interpretation of the observation.Scientific inquiry includes creating a hypothesis through inductive reasoning ... PDF Framing and Solving Problems: using the scientific method representation of the phenomenon or problem •Purposefully: built specifically to solve that particular problem •Simplified: leave out all the unnecessary and trivial details and isolate the important •"All models are wrong, but some are useful." 1 •Know when to stop (once useful, then stop gathering data and running models) 1.1.6: Scientific Problem Solving The scientific method, as developed by Bacon and others, involves several steps: Ask a question - identify the problem to be considered. Make observations - gather data that pertains to the question. Propose an explanation (a hypothesis) for the observations. Make new observations to test the hypothesis further. Scientific Method Science is an enormously successful human enterprise. The study of scientific method is the attempt to discern the activities by which that success is achieved. Among the activities often identified as characteristic of science are systematic observation and experimentation, inductive and deductive reasoning, and the formation and testing of ... Solving Everyday Problems with the Scientific Method Supplementary. This book describes how one can use The Scientific Method to solve everyday problems including medical ailments, health issues, money management, traveling, shopping, cooking, household chores, etc. It illustrates how to exploit the information collected from our five senses, how to solve problems when no information is available ... Scientific Method No matter what the question, you can use the scientific method to guide you towards an answer. Even those questions that do not seem to be scientific can be solved using this process. Like with the flashlight, you might need to repeat several of the elements of the scientific method to find an answer. How to Use the Scientific Method in Everyday Life The scientific method begins with the recognition of a problem and a clear elaboration or description of the problem itself. A process of experimentation and data collection then follows. The final steps consist of the formulation and testing of a hypothesis or potential solution and conclusion. For people unaccustomed to using the scientific ... Solving Everyday Problems with the Scientific Method: Thinking Like a Through this way, The Scientific Method can help readers solve problems in both familiar and unfamiliar situations. Containing real-life examples of how various problems are solved — for instance, how some observant patients cure their own illnesses when medical experts have failed — this book will train readers to observe what others may ... Identifying a Scientific Problem A scientific problem can be solved using the steps of the scientific method. Learn how to identify a scientific problem, how to conduct a scientific experiment, and understand how to choose the ... Using the Scientific Method to Solve Problems The processes of problem-solving and decision-making can be complicated and drawn out. In this article we look at how the scientific method, along with deductive and inductive reasoning can help simplify these processes. ... Using the Scientific Method to Solve Problems How the Scientific Method and Reasoning Can Help Simplify Processes and ... The scientific method (article) The scientific method. At the core of biology and other sciences lies a problem-solving approach called the scientific method. The scientific method has five basic steps, plus one feedback step: Make an observation. Ask a question. Form a hypothesis, or testable explanation. Make a prediction based on the hypothesis. Limitations of the Scientific Method Clearly, the scientific method is a powerful tool, but it does have its limitations. These limitations are based on the fact that a hypothesis must be testable and falsifiable and that experiments and observations be repeatable. This places certain topics beyond the reach of the scientific method. Science cannot prove or refute the existence of ... Solving Everyday Problems with the Scientific Method As such, everyday problems would benefit by employing the scientific method. We will study how the scientific method can be used in daily life. Example. Let us take a look at the wet foot problem discussed in Chapter 1. The father noticed that his daughter stepped only the left foot into the puddle of water. As a result, only the sock and the ... PDF Scientific Method How do Scientists Solve problems Formulate student's ideas into a chart of steps in the scientific method. Determine with the students how a scientist solves problems. • Arrange students in working groups of 3 or 4. Students are to attempt to discover what is in their mystery box. • The group must decide on a procedure to determine the contents of their box and formulate ... The Scientific Revolution (Lesson) Summarize key takeaways from the lesson, emphasizing how the Scientific Method has led to a more systematic and evidence-based approach to knowledge. Reflect on how the Scientific Method has shaped modern knowledge and technology and ask students how they might use the Scientific Method in their own lives or future careers. Homework/Extension. Using the Scientific Method in Everyday Life Scientific method can be described in different ways and some people include slightly different steps, but basically it comes down to these: 1. Make observations. ... Recall some example from your experience where a problem was solved using scientific method. Break down the steps so you can see what hypothesis you formed and how you tested it ... Problems with 'the scientific method' It's a sequence of steps that take you from asking a question to arriving at a conclusion. But scientists rarely follow the steps of the scientific method as textbooks describe it. "The scientific method is a myth," asserts Gary Garber, a physics teacher at Boston University Academy. The term "scientific method," he explains, isn't ... Solving Everyday Problems with the Scientific Method Supplementary. This book describes how one can use The Scientific Method to solve everyday problems including medical ailments, health issues, money management, traveling, shopping, cooking, household chores, etc. It illustrates how to exploit the information collected from our five senses, how to solve problems when no information is available ... Scientific Method For Kids With Examples The scientific method is a valuable tool for introducing kids to a logical way to solve scientific problems. Scientists use the scientific method to study, learn, and come up with an answer! The scientific method is a process that helps double-check that answers are correct and the correct results are obtained through careful planning. 10 Hard Math Problems That May Never Be Solved One of the greatest unsolved mysteries in math is also very easy to write. Goldbach's Conjecture is, "Every even number (greater than two) is the sum of two primes.". You check this in your ... Chronic stress puts your health at risk The long-term activation of the stress response system and too much exposure to cortisol and other stress hormones can disrupt almost all the body's processes. This puts you at higher risk of many health problems, including: Anxiety. Depression. Digestive problems. Headaches. Muscle tension and pain. What Is Artificial Intelligence? Definition, Uses, and Types Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing speech, making decisions, and identifying patterns. AI is an umbrella term that encompasses a wide variety of technologies, including machine learning, deep learning, and ... How to win your consumer dispute using the Elliott Method Avoid these mistakes when using the Elliott Method. If you're using the Elliott Method to solve a consumer complaint, there are some mistakes you should avoid: Don't waste time. Be clear and concise when you explain your problem. Tell the company what you want to happen, like an apology or a voucher. Long, emotional messages are usually ... Save Your Relationship and Try the Scandinavian Sleep Method Tonight Most people use two twin-size comforters or duvets for the Scandinavian sleeping method. This sleeping style typically works best on king mattresses to give the separate blankets the most room ... case study cover letter presentation problem solving rewiew prompts websites tips