Probability for Statistical Inference, Modeling and Data Analysis


Probability models, random variables with discrete and continuous distributions. Marginal, joint, and conditional distributions. Expectations, functions of random variables, central limit theorem. Estimators and sampling distributions, method of moments, and maximum likelihood estimation. Prerequisite: Mathematics 22, 112L, 122, 122L, 202D, 212, 222, or graduate-student standing. Not open to students who have taken Statistical Science 230/Mathematics 230 or Mathematics 340/Statistical Science 231.

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