Introduction to probability with R
 Responsibility
 Kenneth Baclawski.
 Language
 English.
 Imprint
 Boca Raton, FL : Chapman & Hall/CRC, c2008.
 Physical description
 xvi, 363 p. : ill ; 25 cm.
 Series
 Texts in statistical science.
Access
Available online
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QA273 .B2535 2008  Available 
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Creators/Contributors
 Author/Creator
 Baclawski, Kenneth.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 355) and index.
 Contents

 FOREWORD PREFACE Sets, Events, and Probability The Algebra of Sets The Bernoulli Sample Space The Algebra of Multisets The Concept of Probability Properties of Probability Measures Independent Events The Bernoulli Process The R Language Finite Processes The Basic Models Counting Rules Computing Factorials The Second Rule of Counting Computing Probabilities Discrete Random Variables The Bernoulli Process: Tossing a Coin The Bernoulli Process: Random Walk Independence and Joint Distributions Expectations The InclusionExclusion Principle General Random Variables Order Statistics The Concept of a General Random Variable Joint Distribution and Joint Density Mean, Median and Mode The Uniform Process Table of Probability Distributions Scale Invariance Statistics and the Normal Distribution Variance BellShaped Curve The Central Limit Theorem Significance Levels Confidence Intervals The Law of Large Numbers The Cauchy Distribution Conditional Probability Discrete Conditional Probability Gaps and Runs in the Bernoulli Process Sequential Sampling Continuous Conditional Probability Conditional Densities Gaps in the Uniform Process The Algebra of Probability Distributions The Poisson Process Continuous Waiting Times Comparing Bernoulli with Uniform The Poisson Sample Space Consistency of the Poisson Process Randomization and Compound Processes Randomized Bernoulli Process Randomized Uniform Process Randomized Poisson Process Laplace Transforms and Renewal Processes Proof of the Central Limit Theorem Randomized Sampling Processes Prior and Posterior Distributions Reliability Theory Bayesian Networks Entropy and Information Discrete Entropy The Shannon Coding Theorem Continuous Entropy Proofs of Shannon's Theorems Markov Chains The Markov Property The Ruin Problem The Network of a Markov Chain The Evolution of a Markov Chain The Markov Sample Space Invariant Distributions Monte Carlo Markov Chains appendix A: Random Walks Fluctuations of Random Walks The Arcsine Law of Random Walks Appendix B: Memorylessness and ScaleInvariance Memorylessness SelfSimilarity References Index Exercises and Answers appear at the end of each chapter.
 (source: Nielsen Book Data)
 Publisher's Summary
 Based on a popular course taught by the late GianCarlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculusbased introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying website with more information.
(source: Nielsen Book Data)  Supplemental links

Publisher description
Table of contents only
Table of contents
Subjects
Bibliographic information
 Publication date
 2008
 Series
 Chapman & Hall/CRC texts in statistical science series
 Available in another form
 Online version: Baclawski, Kenneth. Introduction to probability with R. Boca Raton, FL : Chapman & Hall/CRC, c2008
 ISBN
 9781420065213 (hardcover : alk. paper)
 1420065211 (hardcover : alk. paper)