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STAT 385. Elementary Statistical Techniques for Machine Learning and Big Data. 3 hours.

Sampling algorithms; nonparametric tests; data mining: classification, clustering, LASSO, cross-validation, Principle Component Regression; and big data analysis focus on R-package. Course Information: Extensive computer use required. Prerequisite(s): Grade of C or better in STAT 382; and consent of the instructor. Students in the BS in Data Science may satisfy the prerequisite with grade of C or better in IDS 462 instead of STAT 382.