Stat 970: Linear Models

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Objective

The objective of this course is to extend our understanding of the standard linear model based approaches. We will make extensive use of matrix algebra. You will therefore need to become comfortable working with matrices. We will also examine the theory behind these methods. You will therefore need to become comfortable with the distributions of linear and quadratic forms. Because this course does not exist in a vacuum, you will need to be able to relate the theory to the application and the application to the theory.

Course Info

Instructor:	Steve Kachman
Office:	354B Hardin Center
Phone:	472-7302
Office Hours:	MWF 10:00-11:00 and by appointment
Text Book:	A First Course in Linear Model Theory, Nalini Ravishanker and Dipak K. Dey
	Website with corrections http://merlot.stat.uconn.edu/~nalini/fcilm.html
Syllabus:	Course Syllabus To view the Course Syllabus click on Course Syllabus . If Acrobat Reader is not installed on your computer click on .
Prerequisites:	Matrix Algebra Distributions Experimental Design Basics of Theory and Inference
Homework:	Approximately once a week 20% will be deducted for each day late.
Exams:	Two exams, will be announced at least one week in advance
Final Exam:	10:00 to 12 noon, Wednesday, May 3 Revise travel plans accordingly.
Check Grades:	Blackboard Course Info

Support Material

• An Introduction to Linear Algebra