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SDS 383C SDSĀ 383C. Statistical Modeling I. 3 Hours.

An introduction to core applied statistical modeling ideas from a probabilistic, Bayesian perspective. Topics include exploratory data analysis, programming in R, Bayesian probability models, an introduction to the Gibbs sampler, applied regression analysis, and hierarchical models. Three lecture hours a week for one semester. Statistics and Data Sciences 383C and Statistics and Scientific Computation 383C may not both be counted. Prerequisite: Graduate standing.