The purpose of this case is to introduce data visualization, advanced regression techniques, and supervised learning. Students are asked to visualize data geographically and in scatterplots. They will use stepwise regression and regression trees to select a predictive model for forecasting data in a holdout sample. In a forecasting competition, they will submit their models to be tested for accuracy. Supervised learning techniques—such as training, validation, and testing—are introduced. Regression trees serve as both predictive and graphical tools for communicating insights from data analysis to a decision maker.
