Includes indexes.

"This self-contained book integrates the use of computers with introductory probability and R, and all new ideas are introduced and illustrated using real computer-related examples. R, the widely-popular software, is not only used as a tool for calculation and data analysis, but also to illustrate the concepts of probability and to simulate distributions. Most examples are related to computing and cover a wide range of computer science applications, including testing program performance, measuring response time and cpu time, estimating the reliability of components and systems, evaluating algorithms and queueing systems, and improving wireless communication. This new edition contains a new chapter on discrete bivariate distributions. This chapter covers distribution of two discrete random variables, joint probabilities, and independence. A Wiley companion site provides data and solutions to problems within the book. Applied examples and exercises in areas in computing that have evolved over the last ten years will be included. Like the first edition, this edition will be primarily addressed to students of computer science and related areas. The second edition will bring this book up to date and will provide extra sections and examples to incorporate new areas of development, such as data mining, machine learning, artificial intelligence, and robotics"-- Provided by publisher

Online resource; title from digital title page (viewed on February 12, 2020).

Includes bibliographical references and index.

Basics of R -- Summarizing statistical data -- Graphical displays -- Probability basics -- Rules of probability -- Conditional probability -- Posterior probability and Bayes -- Reliability -- Introduction to discrete distributions -- The geometric distribution -- The binomial distribution -- The hypergeometric distribution -- The Poisson distribution -- Sampling inspection schemes -- Introduction to continuous distributions -- The exponential distribution -- Queues -- The normal distribution -- Process control -- The inequalities of Markov and Chebyshev.