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Prerequisite: MATH 231. Offered in fall and spring.
Sample space, probability axioms, combinatorial techniques, conditional probability, independence and Bayes' theorem. Random variables; distribution functions, moments and generating functions. Some probability distributions. Joint distribution, the Chebychev inequality and the law of large numbers. The central limit theorem and sampling distributions. Several applications of probability in the social, biological, and engineering sciences are given.
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