Linear Statistical Models

AMS 256 is a graduate level course on linear model theory and multiple regression. Some of the topics covered in this class include: simple and multiple regression, parameter estimation and interpretation, hypothesis testing, prediction, model diagnostics, model comparison and variable selection.

Lectures

Tu-Th 9:50-11:25am Baskin Engineering 169

**Office Hours**

Tu-Th 11:30am-12:30am BE-365C

**Prerequisites**

AMS-205, AMS-205B or permission of the instructor (typically requires AMS 132, AMS 205 or equivalent class)

Books

- Monahan, J.F. (2008) A Primer on Linear Models. Required/Highly Recommended.
- Rencher, A.C. and Schaalje B.G. (2008) Linear Models in Statistics. Wiley-Interscience (Second edition). Highly Recommended.
- Faraway, J.J. (2000) Linear Models with R. Required/Highly Recommended.
- Ravishanker N. and Dey. D (2001) A First Course in Linear Model Theory. Chapman & Hall. Recommended.
- Christensen, R. (2001) Plane answers to complex questions: Theory of linear models. Recommended.

**Homework**

There will be homework assignments roughly every 1.5-2 weeks. Homework assignments will not be graded, but will serve as a study guide for exams.

**Exams**

There will be 3 exams each weighted 1/3 of the total grade. All exams will have an in-class part. They may/may not have a take-home part. There will be no final exam.