This course develops the foundations of predictive modeling by: introducing the conceptual foundations of regression and multivariate analysis; developing statistical modeling as a process that includes exploratory data analysis, model identification, and model validation; and discussing the difference between the uses of statistical models for statistical inference versus predictive modeling.

 

The high level topics covered in the course include: exploratory data analysis, statistical graphics, linear regression, automated variable selection, principal components analysis, exploratory factor analysis, and cluster analysis.

In addition students will be introduced to the SAS statistical software, and its use in data management and statistical modeling.