S730: Theory Of Linear Models
Distribution theory, linear hypothesis, Gauss-Markov theorem, testing and confidence regions. Applications to regression and analysis of variance.
Semester(s) Offered: Spring
Instructor: Chunfeng Huang - firstname.lastname@example.org
Other Contact(s): Chunfeng Huang - email@example.com
Prerequisites: Stat 620
Algebra Required?: For proofs and homework
Calculus Required?: For derivations and homework
Day(s) per week offered: Two lectures a week; no computer labs
Recommended follow-up classes: Most other graduate level statistics courses.
Substantive Orientation: Statistics and Mathematics majors.
Books used: Lecture notes; F. Graybill. 1976. Theory and Application of linear model.; N. Ravishnaker and K. Dey. 2002. A first course in linear model theory.
Software Used: R, SAS
How the software is used: Computation, programming and data analysis.
Problem Sets: Yes, proofs and derivations.
Data Analysis: Yes
Keywords: Theory of linear models