Probability : with applications and R / Amy S. Wagaman and Robert P. Dobrow.

Includes bibliographical references and index.

First principles -- Conditional probability and independence -- Introduction to discrete random variables -- Expectation and more with discrete random variables -- More discrete distributions and their relationships -- Continuous probability -- Continuous distributions -- Densities of functions of random variables -- Conditional distribution, expectation, and variance -- Limits -- Beyond random walks and markov chains.

"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"-- Provided by publisher.