Mathematics of Probability

Daniel W. Stroock

Published by Universities Press, 2020

About this Item

Contents: Preface. 1. Some background and preliminaries. 2. Probability theory on uncountable sample spaces. 3. Some applications to probability theory. 4. The central limit theorem and Gaussian distributions. 5. Discrete parameter stochastic processes. 6. Some continuous-time processes. 7. Martingales. 8. Notation. Bibliography. Index. This book covers the basics of modern probability theory. It begins with probability theory on finite and countable sample spaces and then passes from there to a concise course on measure theory, which is followed by some initial applications to probability theory, including independence and conditional expectations. The second half of the book deals with Gaussian random variables, with Markov chains, with a few continuous parameter processes, including Brownian motion, and, finally, with martingales, both discrete and continuous parameter ones. The book is a self-contained introduction to probability theory and the measure theory required to study it.

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Bibliographic Details

• Title: Mathematics of Probability
• Publisher: Universities Press
• Publication Date: 2020
• Binding: Soft cover
• Condition: New