probability and statistics with applications a problem solving text (second edition) 2015

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Probability and Statistics With Applications: A Problem Solving Text, 2nd Edition

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ISBN: 9781625424723

TITLE: Probability and Statistics With Applications: A Problem Solving Text, 2nd Edition

AUTHOR: Leonard A Asimow and Mark M. Maxwell

PUBLISHER: ACTEX Publications

PUBLISH DATE: 2015

PRICE: $119.00

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Probability and Statistics with Applications : A Problem Solving Text First Edition

• ISBN-10 1566987210
• ISBN-13 978-1566987219
• Edition First Edition
• Publisher ACTEX Publications
• Publication date January 1, 2010
• Language English
• Print length 642 pages
• See all details

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• Publisher ‏ : ‎ ACTEX Publications; First Edition (January 1, 2010)
• Language ‏ : ‎ English
• Paperback ‏ : ‎ 642 pages
• ISBN-10 ‏ : ‎ 1566987210
• ISBN-13 ‏ : ‎ 978-1566987219
• Item Weight ‏ : ‎ 2.95 pounds
• #109,911 in Unknown

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Leonard a. asimow.

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Probability and Statistics With Applications: A Problem Solving Text, 2nd Edition.

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• Chicago style: The Free Library . S.v. Probability and Statistics With Applications: A Problem Solving Text, 2nd Edition.." Retrieved Jun 10 2024 from https://www.thefreelibrary.com/Probability+and+Statistics+With+Applications%3a+A+Problem+Solving+Text%2c...-a0427678612
• APA style: Probability and Statistics With Applications: A Problem Solving Text, 2nd Edition.. (n.d.) >The Free Library. (2014). Retrieved Jun 10 2024 from https://www.thefreelibrary.com/Probability+and+Statistics+With+Applications%3a+A+Problem+Solving+Text%2c...-a0427678612

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Probability & Statistics with Applications: A Problem Solving Text, 2nd Edition

Ph.d., asa leonard a. asimow,ph.d., asa mark m. maxwell.

ISBN-10 : 1625424728

ISBN-13 : 9781625424723

Publisher : ACTEX Publications

Edition : 2nd

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Format : Paperback

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Probability and statistics with applications : a problem solving text

"Probability and Statistics with Applications is an introductory textbook designed to make the subject accessible to college freshmen and sophomores concurrent with their study of calculus"--

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Publication details.

• Probability & statistics with applications : a problem solving text
• Maxwell, Mark M., 1967- author
• Second edition
• Winsted, Connecticut : ACTEX Publications, Inc., [2015]
• ACTEX academic series
• xiii, 745 pages : illustrations (some color) ; 25 cm
• Statement of responsibility from cover.
• Revised edition of the authors' Probability and statistics with applications, 2010.
• Includes index.
• Combinatorial probability -- General rules of probability -- Discrete random variables -- Some discrete distributions -- Calculus and probability -- Some continuous distributions -- Multivariate distributions -- A probability potpourii -- Sampling distributions and estimation -- Hypothesis testing -- Theory of estimation and hypothesis testing -- Appendix I: Statistical tables -- Appendix II: SOA/CAS exam sample questions in text -- Answers to text exercises
• Society of Actuaries -- Examinations -- Problems, exercises, etc.
• Casualty Actuarial Society -- Examinations -- Problems, exercises, etc.
• Mathematical statistics -- Examinations, questions, etc.
• Probabilities.
• Actuarial science -- Examinations, questions, etc.
• Probability Medical Subject Heading

Content Types

• Problems, exercises, etc
• Examinations, questions, etc
• Examens, questions, etc
• Problems and Exercises
• Examinations
• Study guides
• exercise books
• Problems and exercises
• Problèmes et exercices

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ISBN(s): 978-1-62542-837-0 | 978-1-62542-472-3 | 978-1-62542-837-0 | 978-1-63588-299-5

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This textbook is a reference and suggested reading for the SOA Exam P syllabus.

Probability and Statistics with Applications is an introductory textbook designed to make the subject accessible to college freshmen and sophomores concurrent with Calc II and III, with a prerequisite of just one semester of calculus.

It is organized specifically to meet the needs of students who are preparing for the Society of Actuaries qualifying Examination P and Casualty Actuarial Society's Exam MAS-I.

The book provides the content to serve as the primary text for a standard two-semester advanced undergraduate course in mathematical probability and statistics.

Highlights and Details

• Sample actuarial exam problems are integrated throughout the text along with an abundance of illustrative examples and 870 exercises
• Abundance of examples and sample exam problems for both Exams SOA P and CAS MAS-I
• Expansion of statistics portion to cover much of the statistics portion of CAS MAS-I
• Combines best attributes of a solid text and an actuarial exam study manual in one volume
• Widely used by college freshmen and sophomores to pass SOA Exam P early in their college careers
• May be used concurrently with calculus courses
• New or rewritten sections cover topics such as discrete and continuous mixture distributions, non-homogeneous Poisson processes, conjugate pairs in Bayesian estimation, statistical sufficiency, non-parametric statistics, and other topics
• A separate solutions manual for the text exercises is also available

About the Authors

Leonard A. Asimow, Ph.D., ASA

Len joined Robert Morris University in the fall of 2001 as Professor of Mathematics and Actuarial Science, and was the founding Director for the Actuarial Science Program at RMU. The RMU program was designated a Center of Actuarial Excellence in 2010. He has been involved in college-level mathematical instruction, research and administration for more than 50 years, having taught at a variety of institutions including UC Berkeley, UCLA and the University of Wyoming. He has been dedicated to actuarial education since 1988. Dr. Asimow received his bachelor’s degree from UCLA and his doctorate in mathematics from the University of Washington. He previously directed the actuarial science program at Maryville University, St. Louis. Dr. Asimow received his designation as an Associate in the Society of Actuaries in 1990.

Mark M. Maxwell, Ph.D., ASA

Mark joined the faculty at the University of Texas - Austin in the summer of 2009 as Clinical Professor of Mathematics, Paul V. Montgomery fellow, and to direct the UT actuarial program. He served as program director of actuarial science and math department head while collaborating with Dr. Asimow at RMU. Maxwell obtained his undergraduate degree from the College of Idaho and his M.S. and Ph.D. in mathematics from Oregon State University. His teaching methods, publications, professional exam preparation seminars, and this text are designed to help students understand the mathematics and be able to apply their knowledge and techniques. Maxwell was selected for a College of Natural Science Teaching Excellence Award in the Spring of 2014.

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Probability and Statistics with Applications: A Problem Solving Text, (Second Edition) 2015, by Asimow, L. and Maxwell, M., ACTEX, ISBN: 978-1-62542-472-3

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• Publisher ACTEX Publications
• Publication date 2015
• ISBN 10  1625424728
• ISBN 13  9781625424723
• Binding Paperback
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Digital Evaluation Copy

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". . . an excellent textbook . . . well organized and neatly written." — Mathematical Reviews

". . . amazingly interesting . . ." — Technometrics

Thoroughly updated to showcase the interrelationships between probability, statistics, and stochastic processes, Probability, Statistics, and Stochastic Processes , Second Edition prepares readers to collect, analyze, and characterize data in their chosen fields.

Beginning with three chapters that develop probability theory and introduce the axioms of probability, random variables, and joint distributions, the book goes on to present limit theorems and simulation. The authors combine a rigorous, calculus-based development of theory with an intuitive approach that appeals to readers' sense of reason and logic. Including more than 400 examples that help illustrate concepts and theory, the Second Edition features new material on statistical inference and a wealth of newly added topics, including:

Consistency of point estimators

Large sample theory

Bootstrap simulation

Multiple hypothesis testing

Fisher's exact test and Kolmogorov-Smirnov test

Martingales, renewal processes, and Brownian motion

One-way analysis of variance and the general linear model

Extensively class-tested to ensure an accessible presentation, Probability, Statistics, and Stochastic Processes , Second Edition is an excellent book for courses on probability and statistics at the upper-undergraduate level. The book is also an ideal resource for scientists and engineers in the fields of statistics, mathematics, industrial management, and engineering.

PETER OLOFSSON , PhD, is Professor in the Mathematics Department at Trinity University. Dr. Olofsson's research interests include stochastic processes, branching processes, mathematical biology, and Poisson approximation. He is the author of Probabilities: The Little Numbers That Rule Our Lives , also published by Wiley.

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Probability and Statistics for Machine Learning

• © 2024
• Charu C. Aggarwal 0

IBM T. J. Watson Research Center, Yorktown, USA

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• Simple and intuitive discussions of probability and statistics
• Discusses details of applications of mathematical concepts to machine learning
• Provides mathematical details without losing the reader in complexity

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About this book

This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:

1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5.

2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.

3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations.

The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners.

• Machine learning
• Artificial Intelligence
• Probability
• Data Mining

Table of contents (11 chapters)

Front matter, probability and statistics: an introduction.

Charu C. Aggarwal

Summarizing and Visualizing Data

Probability basics and random variables, probability distributions, hypothesis testing and confidence intervals, reconstructing probability distributions from data, classification: a probabilistic view, unsupervised learning: a probabilistic view, discrete state markov processes, probabilistic inequalities and approximations, back matter, authors and affiliations, about the author, bibliographic information.

Book Title : Probability and Statistics for Machine Learning

Book Subtitle : A Textbook

Authors : Charu C. Aggarwal

DOI : https://doi.org/10.1007/978-3-031-53282-5

Publisher : Springer Cham

eBook Packages : Mathematics and Statistics , Mathematics and Statistics (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

Hardcover ISBN : 978-3-031-53281-8 Published: 15 May 2024

Softcover ISBN : 978-3-031-53284-9 Due: 15 June 2024

eBook ISBN : 978-3-031-53282-5 Published: 14 May 2024

Edition Number : 1

Number of Pages : XVIII, 522

Number of Illustrations : 1 b/w illustrations

Topics : Machine Learning

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