Elementary Probability for Applications

Rick Durrett

doi:10.1017/CBO9780511841521

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.

‘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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Elementary Probability for Applications

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Contents

Frontmatter
pp i-iv

Contents
pp v-vi

Preface
pp vii-x

1 - Basic Concepts
pp 1-31

2 - Combinatorial Probability
pp 32-80

3 - Conditional Probability
pp 81-113

4 - Markov Chains
pp 114-160

5 - Continuous Distributions
pp 161-189

6 - Limit Theorems
pp 190-228

7 - Option Pricing
pp 229-236

Normal Table
pp 237-238

Index of Terms
pp 239-240

Index of Examples
pp 241-241

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