A First Course in Linear Model Theory

This innovative, intermediate-level statistics text fills an important gap by presenting the theory of linear statistical models at a level appropriate for senior undergraduate or first-year graduate students. The authors' approach introduces readers to the mathematical and statistical concepts and tools, from matrix algebra, linear algebra, and distribution theory that form the backbone for studying the theory and applications of linear models, both univariate and multivariate. It also leads readers through the invaluable first step in their studies of advanced linear models, generalized linear models, nonlinear models, and dynamic models.