Instructor: Kenny Ye, 1-117 Math, 632-9344, kye@ams.sunysb.edu
Lectures:  3:50 - 5:10 MW
Location: Physics P127 (will be moved)
Office Hours: 1:30-2:30 MW

TA: Paul Yoon, TuTh 2-3pm. Phy B-148
Email: cyoon@ams.sunysb.edu

Prerequisite: Basic knowledge in regression analysis and ANOVA, estimation and statistical testing.

Topic to be covered:
1. Estimation and Inference of Linear Regression Models
2. Generalized Least Squares
3. Measurement Error Model
4. Diagnostics
5. Transformation
6. Variable Selection
7. Principle Components and Collinearity
8. Missing Data

Textbook and Reference
1. ``Practical Regression and Anova using R" by Julian Faraway. It is yet to be published.
2. ``Regression Analysis" by Sen and Srivastava
3. ``Applied Regression Including Computing and Graphics" by Cook and Weisberg
4. ``Modern Applied Statistics with S-Plus'' by Venables and Ripley

Homework Assignments

Data Library I used for Lection: faraway.zip

R-Scripts in Lecture

March 8
March 11
March 15
March 17
March 22
March 24
March 29
April 12
April 14

My Version of Proof of Gauss-Markov Theorem

• R Official Site
• S+ Official Site
• Free Student Version of S-Plus
• Notes on S-Plus, A programming environment for data analysis and graphic
• Library MASS
• precompiled R library Leaps for Windows. (Provided by Duncan Murdoch).
• Official S-Plus Manual (1, 2, 3 )
• Old Exam (Solution)

Grading is based on weekly homework assignment (50%)  and Midterm (50%), there will be no final exam.