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

Marlene A Smith
The American Statistician,Vol. 65, Issue 3, Pages: 190-197.

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. …
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