Probability: Theory and Examples, 4th Edition

Probability: Theory and Examples (Cambridge Series in Statistical and Probabilistic Mathematics)
This book is an introduction to probability theory covering 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.

Table of Contents

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
Appendix A. Measure theory details.