Modern and measure-theory based, this text is intended primarily for the first-year graduate course in probability theory.
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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.
Ph.D. Stanford University
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Hardcover. Condition: Très bon. Ancien livre de bibliothèque avec équipements. Edition 1996. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1996. Ammareal gives back up to 15% of this item's net price to charity organizations. Seller Inventory # G-126-572
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Hard cover. Condition: Good. No jacket. Spine cocked, some rubbing on covers. Corners and edges worn, some superficial separation of title page from binding. Clean and unmarked in main text. Seller Inventory # 1131799
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