Covers regression diagnostics for linear models, emphasizing the importance of checking assumptions and identifying outliers and influential observations.
Explores extreme values in random variables, applications in environmental factors, reliability modeling, block maxima distribution, and the Generalized Extreme Value distribution.
Covers fractional factorial designs to efficiently study interactions in experiments, focusing on aliasing, geometric interpretation, and effect selection.
