Unlock the world of linear models with “A First Course in Linear Model Theory, Second Edition.” This essential statistics text, perfect for senior undergraduates and graduate students, bridges the gap in understanding multivariate and univariate linear models. Updated and expanded, this edition features three new chapters covering generalized linear models, Bayesian and hierarchical models, and regularized regression. It delves deeper into random and mixed effects models, model selection, and multiple comparisons, integrating practical R functionality for data illustrations. The authors’ innovative approach, clear presentation, and comprehensive examples make this an invaluable first step for mastering advanced statistical modeling. Discover the latest methodologies and solidify your foundation in statistical science with this definitive guide.