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Starting with the elementary rules of probability, Probability and Statistics for Computer Scientists presents topics widely used in modern computer science. The author explores stochastic processes, Markov chains, queuing theory, and Monte Carlo methods, followed by statistical inference, estimation, testing, regression, and model fitting. Coverage also includes computer simulation techniques and their implementation in MATLABŪ. A large number of motivating examples and exercises show applications to computer science, software engineering, and other fields. The text is designed for a one-semester calculus-based course at the junior/senior undergraduate level.