Probability: Theory and Examples

Front Cover
Cambridge University Press, Aug 30, 2010 - Mathematics
3 Reviews
This classic introduction to probability theory for beginning graduate students covers laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. It is a comprehensive treatment concentrating on the results that are the most useful for applications. Its philosophy is that the best way to learn probability is to see it in action, so there are 200 examples and 450 problems. The new edition begins with a short chapter on measure theory to orient readers new to the subject.

What people are saying - Write a review

User Review - Flag as inappropriate

Hydraulic Enge

Review: Probability: Theory and Examples

User Review  - Xing Shi - Goodreads

I like the book because it usually gives proof for theorems in more generalized forms, but I really don't like the typos in the electronic version. I'm not sure about the printed version, but if it's the same the electronic one, then an errata is definitely needed. Read full review


1 Measure Theory
2 Laws of Large Numbers
3 Central Limit Theorems
4 Random Walks
5 Martingales
6 Markov Chains
7 Ergodic Theorems
8 Brownian Motion
Measure Theory Details

Common terms and phrases

About the author (2010)

Rick Durrett received his Ph.D. in Operations Research from Stanford University in 1976. After nine years at UCLA and twenty-five 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.

Bibliographic information