Statistics 230A        Linear Models

Course Description

We will cover the theory and applications of linear statistical models. We will try to gain understanding and insight through algebraic and geometric approaches to the theory and by using the computer to analyze real and simulated data.  Applications and computational aspects will treated using the statistical language R.  I plan to cover the following topics:

Grades will be based on a midterm, a final exam, regular homework, and computer labs.


Pre-requisites: Statistics 135, 200B or an equivalent course in statistics at a post-calculus level. Linear algebra.


Texts:  Several books will be on course reserve in the Mathematics and Statistics Library. I recommend two in particular:


John Rice
Office:  425 Evans Hall
Phone:  642-6930
Email: rice "at"

Office hours: Wed 2-4



Greg Hather

Office: 437 Evans

Email: ghather "at"

Office hours: Th 2-4

Lab homepage




Tu-Thu 12:30-2:00. 332 Evans

Lab Section

Mon 10-12. 332 Evans

Additional Material

The R Project for Statistical Computing   You can download the software we will use for this class from this site.

Oleg Mayba's concise notes on linear algebra

Charlotte Wickham's concise notes on linear models.

Phil Spector's Introduction to R and R Tutorial


Homework 1 due September 7 solutions

Homework 2 due September 14 solutions

Homework 3 due September 21 solutions

Homework 4 due October 3 solutions

Homework 5 due October 12 solutions bodytemp.csv

Homework 6 due October 19 solutions oldfaithful.csv

Homework 7 due November 28 solutions