MATH 550 Linear Models (3)

This course provides an introduction to the theory of linear models for analyzing data. Topics include analysis of variance and regression models, as well as Bayesian estimation, hypothesis testing, multiple comparison, and experimental design models. Additional topics such as balanced incomplete block designs, testing for lack of fit, testing for independence, and variance component estimation are also treated. The approach taken is based on projections, orthogonality, and other vector space concepts.
Prerequisite(s): Students must have a working knowledge of undergraduate Linear Algebra and Statistics.
Course Frequency: Fall