Assess learners' ability to analyze residuals and apply diagnostic tests in simple and multiple linear regression models: interpret residual vs fitted and QQ plots, evaluate assumptions (linearity, independence, homoscedasticity, normality) using tests such as Durbin–Watson, Breusch–Pagan, and Shapiro–Wilk, detect influential observations with leverage and Cook's distance, and recommend appropriate remedial actions (transformations, weighted or robust regression, model re-specification).