Probability: Theory and Examples
by Rick Durrett
Publisher: Cambridge University Press 2010
Number of pages: 372
This book is an introduction to probability theory covering 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.
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by Yuen-Kwok Chan - arXiv.org
The author provides a systematic, thorough treatment of the foundations of probability theory and stochastic processes along the lines of E. Bishop's constructive analysis. Every existence result presented shall be a construction ...
by C. M. Grinstead, J. L. Snell - American Mathematical Society
The textbook for an introductory course in probability for students of mathematics, physics, engineering, social sciences, and computer science. It presents a thorough treatment of techniques necessary for a good understanding of the subject.
by Robert B. Ash - Dover Publications
This text surveys random variables, conditional probability and expectation, characteristic functions, infinite sequences of random variables, Markov chains, and an introduction to statistics. Geared toward advanced undergraduates and graduates.
by David Nualart - The University of Kansas
From the table of contents: Stochastic Processes (Probability Spaces and Random Variables, Definitions and Examples); Jump Processes (The Poisson Process, Superposition of Poisson Processes); Markov Chains; Martingales; Stochastic Calculus.