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This fourth-edition textbook offers a rigorous, graduate-level introduction to measure-theoretic probability. It covers foundations such as measure theory and integration, and develops core topics including the laws of large numbers, central limit theorems, random walks, martingales, Markov chains, ergodic theorems, and Brownian motion. The book emphasizes learning through practice, with about 200 examples and 450 exercises to help readers internalize both theory and applications

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245: $a: Probability: Theory and Examples
245: $b:
082: $a:
100: $a: RICK DURRETT
650: $a: Mathematics
250: $a:
440: $v:
250: $b: Cambridge University Press
250: $c: 2010
020: $a: 9780521765398
300: $a: 440