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 Title: Elementary Probability for Applications
 Author(s) Rick Durrett
 Publisher: Cambridge University Press, 1st Edition (2009); eBook (Draft, 3rd Edition, April 2021)
 Permission: The PDF Draft is post by the author.
 Hardcover 254 pages
 eBook PDF (163 pages)
 Language: English
 ISBN10/ASIN: 0521867568
 ISBN13: 9780521867566
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Book Description
This clear and lively introduction to probability theory concentrates on the results that are the most useful for applications, including combinatorial probability and Markov chains.
Concise and focused, it is designed for a onesemester introductory course in probability for students who have some familiarity with basic calculus. Reflecting the author's philosophy that the best way to learn probability is to see it in action, there are more than 350 problems and 200 examples.
The examples contain all the old standards such as the birthday problem and Monty Hall, but also include a number of applications not found in other books, from areas as broad ranging as genetics, sports, finance, and inventory management.
The book has a nice interplay between probability modeling and scientific applications, whether from biology, sports, or discussions of China's onechild policy. Many of the examples are thought provoking, including ones on DNA samples for paternity cases and others about the O.J. Simpson trial. And the large selection of interesting problems builds basic skills and deepens or extends the main ideas.
About the Authors Rick Durrett received his Ph.D. in Operations Research from Stanford University in 1976. After nine years at UCLA and twentyfive at Cornell University, he moved to Duke University in 2010, where he is a Professor of Mathematics. He is the author of 8 books and more than 170 journal articles on a wide variety of topics, and he has supervised more than 40 Ph.D. students. He is a member of the National Academy of Science and the American Academy of Arts and Sciences and a Fellow of the Institute of Mathematical Statistics.
 Probability, Stochastic Process, Queueing Theory, etc.
 Statistics and SAS Programming
 Financial Mathematics and Engineering
 Computational and Algorithmic Mathematics
 Combinatorics and Game Theory

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