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Linear models form the foundation of a vast range of statistical methodologies. Julian J. Faraway's critically acclaimed Linear Models with R thoroughly examined the different methods available, and showed in which situations each one applies. Following in those footsteps, his new book surveys the techniques that grow from the regression model, presenting three extensions to that framework: generalized linear models, mixed effect models, and nonparametric regression models. It provides a well-stocked toolbox of methodologies, and with its unique presentation of these very modern statistical techniques, holds the potential to break new ground in the way graduate-level courses in this area are taught.