A Teaching Note for Model Selection and Validation

Abstract

The model selection problem is always crucial for any decision making in statistical research and management. Among the choice of many competing models, how to decide the best is even more crucial for researchers. This small article is prepared as a teaching note for deciding an appropriate model for a real-life data set. We briefly describe some of the existing methods of model selection. The best model from the two competing models is decided based on the comparison of the limited expected value function (LEVF) or loss elimination ratio (LER). A data set is analyzed through MINITAB software.