Missteps in Multiple Regression Student Projects: Beyond Association-Not-Causation

摘要

This article describes common yet subtle errors that students make in self-designed multiple regression projects, based on experiences in a graduate business statistics course. Examples of common errors include estimating algebraic identities, overlooking suppression, and misinterpreting regression coefficients. Advice is given to instructors about helping students anticipate and avoid these common errors; recommended tactics include extensive written guidelines supplemented with in-class active-learning exercises. Several examples using real data are provided. Brief mention is made of incorporating these activities into online courses. Because self-designed student projects require significant effort from students and faculty, anticipating these common errors, and helping students circumvent them, can go a long way to making student projects a more satisfying experience for all.