Assumptions in Linear Regression

Our regression model makes the same assumptions as all linear models. This includes the assumption that the unexplained variability around the regression line—the residual differences—is approximately normal and has constant variance. We can check these assumptions with the same graphical methods that we used to analyze Darwin’s maize data. The residuals are the differences between the observed data and the model’s fitted (predicted) values.