Use and Interpretation of Multiple Regression (original) (raw)

This article discusses the application and interpretation of multiple regression analysis in research, particularly highlighting its use in understanding complex relationships between multiple independent variables and a dependent variable. Using an example from Logan and King's study, it explains how multiple regression helps to quantify relationships and predict outcomes, emphasizing important statistical measures like the Pearson correlation coefficient and the coefficient of determination (r2). The discussion contextualizes how multiple regression can uncover underlying relationships and the limitations of interpretation regarding causation.