Stats 851.3 A rigorous development of the general linear
model, using vector space theory. Generalized inverses, orthogonal projections,
quadratic forms, Gauss-Markov theorem, estimability.
Stats 443.3 A rigorous examination of the general linear
model using vector space theory. Includes: generalized inverses; orthogonal
projections; quadratic forms; Gauss-Markov theorem and its generalizations; BLUE
estimators; Non-full rank models; estimability considerations.
Suggested
Bibliography
Assignment 3 (due Wednesday February 8)
Lectures
1. Introduction Review of Linear Algebra, pdf
2. Review of Probability and Statistics, pdf
3. The General Linear Model, pdf
4. The GLM - Testing and Confidence Intervals, pdf
5. The GLM - More general Assumptions, pdf
6. The GLM - Summary, pdf
7. The GLM - Applications, pdf
8. ANOVA, Experimental Design Models, pdf
9. Selecting the Best Equation, pdf
10. Examination of Residuals, pdf
11. Some Examples, pdf
12. Non-Linear Models, pdf