This is a textbook for a one-semester graduate course in measure-theoretic probability theory, but with ample material to cover an ordinary year-long course at a more leisurely pace. Khoshnevisan's approach is to develop the ideas that are absolutely central to modern probability theory, and to showcase them by presenting their various applications. As a result, a few of the familiar topics are replaced by interesting non-standard ones. The topics range from undergraduate probability and classical limit theorems to Brownian motion and elements of stochastic calculus. Throughout, the reader will find many exciting applications of probability theory and probabilistic reasoning. There are numerous exercises, ranging from the routine to the very difficult. Each chapter concludes with historical notes.
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978-0-8218-4215-7 (9780821842157)
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Schweitzer Klassifikation
Classical probability Bernoulli trials Measure theory Integration Product spaces Independence The central limit theorem Martingales Brownian motion Terminus: Stochastic integration Background material Bibliography Index.
