STA 5320 - Linear Statistical Models (3)

Review of selected linear algebra and probability background material, including projection matrices and the multivariate normal distribution; matrix formulation of the multiple linear regression model, estimation, hypothesis testing, predictions, restrictions, and rank deficiency; one-way, two-way, and higher-way analysis of variance, random effects and variance components; illustration with statistical software and matrix computation software such as R or MATLAB.

Prerequisite(s): STA 4320 and MAT 2250; or STA 432 and MAT 2250; or STA 4320 and MAT 208; or STA 432 and MAT 208.
Component(s): Lecture
Grading Basis: Graded Only
Repeat for Credit: May be taken only once