Instructor:

Prof. J. Taylor
Sequoia Hall #137
Email
7239230

Schedule:

TTh 1:152:30

Location:

540108

Office Hours:

TTh 2:303:30

Textbooks:

 Introduction to Linear Regression
Analysis. D. Montgomery, E. Peck. (optional)
 Modern Applied Statistics with S. D. Venables,
B. Ripley. (optional)

TAs & Office Hours:


Tentative
schedule:

Schedule

General
Outline:

The course is intended to be a (nonexhaustive) survey of regression techniques from both a theoretical and applied perspective. Time permitting, the types of models we will study include:
 Simple Linear Regression
 Multiple Linear Regression
 Polynomial Regression
 Model Selection for Mupltiple Linear Models
 Multiple Linear Regression  Diagnostics
 Analysis of Variance: Fixed Effects
 Experimental Design
 Penalized Regression
 Robust Regression
 Nonlinear Regression
 Generalized Linear Models
 Mixed Effects Models
 Time Series Regression: Correlated Errors
 Functional Linear Models
 Additive Models

Pre(co)requisites: 
STATS 200. Familiarity with matrix algebra will also be helpful.

Evaluation:

 4 assignments: 60%
 1 take home final project 40%

Assignments:


Notes:

 Course Introduction, R
 Diagnostics, R
 Multiple Linear Regression, R
 Polynomial Regression, R
 Diagnostics, R
 Model Selection, R
 Analysis of Variance, R
 Experimental Design
 Penalized Regression, R
 Robust Regression, R
 Nonlinear Regression, R
 Generalized Linear Models I
 Generalized Linear Models II
 Fixed vs. Random Effects, R
 Mixed Effects Models, R
 Time Series, R
 Time Series Regression, R
 Functional Data
 Review
