Category Archives: Violating Assumptions

Introduction (PDF & R-Code) Satisfying the assumption of linearity in an Ordinary Least Squares (OLS) regression model is vital to the development of unbiased slope coefficients, standardized coefficients, standard errors, and the model R2. Simply put, if a non-linear relationship exists, the estimates produced from specifying a linear association between two variables will be biased.Continue reading “Entry 1: The Linearity Assumption”