Understanding Probability Using everyday examples to demystify probability, this classic is now in its third edition with new chapters, exercises and examples. Henk Tijms (Author) 9781107658561, Cambridge University Press Paperback / softback, published 14 June 2012 574 pages, 60 b/w illus. 520 exercises22.6 x 15.2 x 3.3 cm, 0.9 kg 'This book distinguishes itself with its down-to-earth style. Covering a wide range of topics from probability, it is filled with real-world fun examples that vividly illustrate sophisticated theory with simplicity. This new expanded edition could now serve as an excellent introductory textbook on probability theory at the undergraduate and masters level.' Karl Sigman, Columbia University Understanding Probability is a unique and stimulating approach to a first course in probability. The first part of the book demystifies probability and uses many wonderful probability applications from everyday life to help the reader develop a feel for probabilities. The second part, covering a wide range of topics, teaches clearly and simply the basics of probability. This fully revised third edition has been packed with even more exercises and examples and it includes new sections on Bayesian inference, Markov chain Monte-Carlo simulation, hitting probabilities in random walks and Brownian motion, and a new chapter on continuous-time Markov chains with applications. Here you will find all the material taught in an introductory probability course. The first part of the book, with its easy-going style, can be read by anybody with a reasonable background in high school mathematics. The second part of the book requires a basic course in calculus. Preface Introduction Part I. Probability in Action: 1. Probability questions 2. The law of large numbers and simulation 3. Probabilities in everyday life 4. Rare events and lotteries 5. Probability and statistics 6. Chance trees and Bayes' rule Part II. Essentials of Probability: 7. Foundations of probability theory 8. Conditional probability and Bayes 9. Basic rules for discrete random variables 10. Continuous random variables 11. Jointly distributed random variables 12. Multivariate normal distribution 13. Conditioning by random variables 14. Generating functions 15. Discrete-time Markov chains 16. Continuous-time Markov chains Appendix Counting methods and ex Recommended reading Answers to odd-numbered problems Bibliography Index. Subject Areas: Stochastics [PBWL], Probability & statistics [PBT], Calculus [PBKA], Mathematics [PB]
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