Theory of Linear Models

Provides an introduction to the development and use of general linear models including frameworks for parameter estimation and inference in a variety of settings. Theoretical foundations of the models will be reinforced with areas in which the models are applied to answer scientific questions. Topics covered include matrix algebra, distribution theory for quadratic forms of normal random vectors, properties of OLS estimators, estimable functions and related themes.