Analysis of large business data sets via statistical summaries, cross-tabulation, correlation, and variance matrices. Techniques in model selection, prediction, and validation utilizing general linear and logistic regression, Bayesian methods, clustering, and visualization. Extensive programming in R is expected.
Prerequisites: Calculus, Statistics, and Programming knowledge.
Course Component(s): Lecture
For live class lectures, you will log in using the Zoom UM System link in Canvas. For accessing class recordings, you will need to contact your instructor directly.
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