ABSTRACT

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.

chapter 1|12 pages

Examples of the General Linear Model

chapter 2|24 pages

The Linear Least Squares Problem

chapter 3|34 pages

Estimability and Least Squares Estimators

chapter 4|28 pages

Gauss–Markov Model

chapter 5|26 pages

Distributional Theory

chapter 6|32 pages

Statistical Inference

chapter 7|24 pages

Further Topics in Testing

chapter 8|26 pages

Variance Components and Mixed Models

chapter 9|30 pages

The Multivariate Linear Model