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 one-semester 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.
- Over 350 exercises and 200 examples
- Can be used by students who do not know much calculus
- Covers Markov chains
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Reviews & endorsements
'The book has a nice interplay between probability modeling and scientific applications, whether from biology, sports, or discussions of China's one-child policy. Many of the examples are thought provoking, including ones on DNA samples for paternity cases and others about the O. J. Simpson trial. As an instructor, I enjoy digging into these examples in class. And the large selection of interesting problems builds basic skills and deepens or extends the main ideas.' Professor Michael Phelan, University of California, Irvine

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Product details
- Date Published: July 2009
- format: Hardback
- isbn: 9780521867566
- length: 254 pages
- dimensions: 255 x 195 x 18 mm
- weight: 0.66kg
- contains: 55 b/w illus. 80 tables 355 exercises
- availability: Available
Table of Contents
1. Basic concepts
2. Combinatorial probability
3. Conditional probability
4. Markov chains
5. Continuous distributions
6. Limit theorems
7. Option pricing.
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Instructors have used or reviewed this title for the following courses
- Advanced Probability
- An Introduction to Probability
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- Element of Statistics
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- Theory of Probability
Author
Rick Durrett, Duke University, North Carolina
Rick Durrett received his Ph.D. in operations research from Stanford University in 1976. After nine years at UCLA, he came to Cornell University in 1985, 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, American Academy of Arts and Sciences, and a Fellow of the Institute of Mathematical Statistics.