Newly revised by the author, this undergraduate-level text introduces the mathematical theory of probability and stochastic processes. Subjects include sample spaces, probabilities distributions and expectations of random variables, conditional expectations, Markov chains, the Poisson process; continuous-time stochastic processes; much more. Features worked examples as well as exercises and solutions. Republication of the revised second edition, originally published by The Benjamin/Cummings Publishing Company, Inc., 1988.
Here's a sample of other books in this Dover category
Stochastic Finite Elements: A Spectral Approach by Roger G. Ghanem, Pol D. Spanos This text analyzes a class of discrete mathematical models of engineering systems, identifying key issues and reviewing relevant theoretical concepts, with particular attention to a spectral approach. 1991 edition.
Applied Probability Models with Optimization Applications by Sheldon M. Ross Concise advanced-level introduction to stochastic processes that arise in applied probability. Poisson process, renewal theory, Markov chains, Brownian motion, much more. Problems. References. Bibliography. 1970 edition.
Nonstandard Methods in Stochastic Analysis and Mathematical Physics by Sergio Albeverio, Jens Erik Fenstad, Raphael Høegh-Krohn, Tom Lindstrøm Two-part treatment begins with a self-contained introduction to the subject, followed by applications to stochastic analysis and mathematical physics. "A welcome addition." — Bulletin of the American Mathematical Society. 1986 edition.
Distributions: An Outline by Jean-Paul Marchand Rigorous and concise, this text examines the basis of the distribution theories devised by Schwartz and by Mikusinki and surveys both functional and algebraic theories of distribution. 1962 edition.