• Homogeneity of variance. Strictly speaking, the regression model assumes that each residual ϵi is generated from a normal distribution with mean 0, and (more importantly for the current purposes) with a standard deviation σ that is the same for every single residual. In practice, it’s impossible to test the assumption that every residual is identically distributed. Instead, what we care about is that the standard deviation of the residual is the same for all values of $$\ \hat{Y}$$, and (if we’re being especially paranoid) all values of every predictor X in the model. See Section 15.9.5.