Probability - 2nd Edition by Amy S Wagaman & Robert P Dobrow (Hardcover)

About the Book

"This book is ideal for courses on Probability typically taught in Mathematics and/or Statistics departments but could also be used in Engineering or Data Science departments. This book could also serve as a supplemental or review text for courses on Stochastic Processes or Markov Chains or Brownian Motion, since those require a strong foundation in probability. The text is also preparatory for the Probability Actuarial Exam -- students who successfully complete a course with this text and do well are well-positioned to pass the P exam. Some major features of the new edition include an addition of supplemental materials for coding and simulation, improved exposition and examples for some topics, and addressing issues with errata. These features increase the value of the text especially in an era where developing computing skills has become a staple of statistical practice, and desirable for many other fields as well"--

Book Synopsis

Discover the latest edition of a practical introduction to the theory of probability, complete with R code samples

In the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program.

New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn't include them in the first edition.

The new edition also includes for the first time:

• A thorough discussion of reproducibility in the context of generating random numbers
• Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs
• Substantial organizational changes to improve the flow of the material
• Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculus

Perfect for upper-level undergraduate students in a first course on probability theory, Probability With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.

From the Back Cover

Discover the latest edition of a practical introduction to the theory of probability, complete with R code samples

In the newly revised Second Edition of Probability: With Applications and R, distinguished researchers Drs. Robert Dobrow and Amy Wagaman deliver a thorough introduction to the foundations of probability theory. The book includes a host of chapter exercises, examples in R with included code, and well-explained solutions. With new and improved discussions on reproducibility for random numbers and how to set seeds in R, and organizational changes, the new edition will be of use to anyone taking their first probability course within a mathematics, statistics, engineering, or data science program.

New exercises and supplemental materials support more engagement with R, and include new code samples to accompany examples in a variety of chapters and sections that didn't include them in the first edition.

The new edition also includes for the first time:

• A thorough discussion of reproducibility in the context of generating random numbers
• Revised sections and exercises on conditioning, and a renewed description of specifying PMFs and PDFs
• Substantial organizational changes to improve the flow of the material
• Additional descriptions and supplemental examples to the bivariate sections to assist students with a limited understanding of calculus

Perfect for upper-level undergraduate students in a first course on probability theory, Probability: With Applications and R is also ideal for researchers seeking to learn probability from the ground up or those self-studying probability for the purpose of taking advanced coursework or preparing for actuarial exams.

About the Author

Amy S. Wagaman, PhD, is Associate Professor of Statistics at Amherst College. She received her doctorate in Statistics at the University of Michigan in 2008. Her research interests include nonparametric statistics, statistics education, dimension reduction and estimation, and covariance estimation and regularization.

Robert P. Dobrow, PhD, is Emeritus Professor of Mathematics at Carleton College. He has over 15 years of experience teaching probability and has authored numerous papers in probability theory, Markov chains, and statistics.