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.

The case is intended for a class relatively early in a decision analysis or a risk analysis class module. The case can be used as the very first case in the course if students are familiar with the concepts of NPV. Alternatively, students can be given a short technical note on calculating NPV for cash flows as pedagogy for the case. The analysis requires use of NPV calculations to determine the outcomes of different options in the case and to choose one of the given options. Using the choices that students make, the instructor can lead a rich discussion on effects of risk-seeking and risk-averse behavior in situations that managers face in real life.

Student spreadsheet to case UV6468