Probability Theory for Data Science

Topics include introducing common random variable models, the central limit theorem, law of large numbers, random variable convergence. Topics may also include order statistics, probability inequalities, Slutsky’sTheorem, Markov chains and stochastic gradient descent. Probability computation using modern software. Not open to students who are taking or who have received credit for MATH 640.

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