Indiana University Bloomington

Statistics S730
Theory Of Linear Models

Contact: Chunfeng Huang ( 2012-10-23
Offered: Spring,
Capacity: 30
Sequence: no
Pre-Requisites: Stat 620
Algebra Required: For proofs and homework.
Calculus Required: For derivations and homework.
Instructor: Chunfeng Huang
Days Per Week Offered: Two lectures a week; no computer labs
Recommended follow-up classes: Most other graduate level statistics courses.
Syllabus: No Syllabus Avaliable
Keywords: Theory of linear models
Description: Distribution theory, linear hypothesis, Gauss-Markov theorem, testing and confidence regions. Applications to regression and analysis of variance.
Books: Lecture notes; F. Graybill. 1976. Theory and Application of linear model.; N. Ravishnaker and K. Dey. 2002. A first course in linear model theory.
Substantive Orientation: Statistics and Mathematics majors.
Applied/Theoretical: Theoretical
Software: R, SAS
How Software is Used: Computation, programming and data analysis.
Problem Sets: Yes, proofs and derivations.
Data Analysis: Yes.
Presentation: Yes.
Exams: No.