Prerequisite: STAT 102 OR STAT 112 OR STAT 431 This course may be taken concurrently with the prerequisite with instructor permission.
Classical And Modern Regression With Applications Pdf Download software#
The methodologies can all be implemented in either the JMP or R software packages. By the end of the course the student will be familiar with and have applied all these tools and will be ready to use them in a work setting. It also introduces classification and regression trees (CART) and the popular predictive methodology known as the random forest. It delves into classification methodologies such as logistic regression. In particular it introduces automated model selection tools, such as stepwise regression and various current model selection criteria such as AIC and BIC.
It extends the ideas from regression modeling, focusing on the core business task of predictive analytics as applied to realistic business related data sets. This course follows from the introductory regression classes, STAT 102, STAT 112, and STAT 431 for undergraduates and STAT 613 for MBAs. STAT 422 Predictive Analytics for Business
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