Model Checking and ResidualsExplores model checking and residuals in regression analysis, emphasizing the importance of diagnostics for ensuring model validity.
Regression DiagnosticsCovers regression diagnostics for linear models, emphasizing the importance of checking assumptions and identifying outliers and influential observations.
Nested Model SelectionExplores nested model selection in linear models, comparing models through sums of squares and ANOVA, with practical examples.
Geometry and Least SquaresDiscusses the geometry of least squares, exploring row and column perspectives, hyperplanes, projections, residuals, and unique vectors.