Probability: Theory and Examples / Edition 1by Richard A. Durrett
Pub. Date: 10/28/1990
Modern and measure-theory based, this text is intended primarily for the first-year graduate course in probability theory. See more details below
Modern and measure-theory based, this text is intended primarily for the first-year graduate course in probability theory.
- Publication date:
- The Wadsworth & Brooks/cole Statistics/probability Series
- Edition description:
- Older Edition
- Product dimensions:
- 7.09(w) x 9.84(h) x (d)
Table of ContentsIntroductory Lecture. 1. Laws of Large Numbers. 2. Central Limit Theorems. 3. Random Walks. 4. Martingales. 5. Markov Chains. 6. Ergodic Theorems. 7. Brownian Motion. Appendix: Measure Theory. References. Notation. Normal Table. Index.
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