*****COURSES ARE SUBJECT TO CHANGE*****
Introduction to fundamental tools of stochastic analysis. Probability, conditional probability, Bayes Theorem, random variables, independence, Poisson processes, Bernnoulli trials, and Markov chains. Instructor's choice of additional topics, most likely drawn from confidence measures, difference equations, transform methods, stability issues, applications to reliability, queues, and hidden Markov models. Students cannot receive credit for this course and Applied Mathematics and Statistics 131. Prerequisite(s): course 16 or 16H and Mathematics 22 or 23A. (General Education Code(s): SR.) A. Brandwajn, R. Manduchi, JJ Garcia-Luna-Aceves
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