stats203

Introduction to Regression Models and Analysis of Variance

Instructor:
Prof. J. Taylor
Sequoia Hall #137
Email
723-9230

Schedule:
TTh 1:15-2:30
Location:
540-108
Office Hours:
TTh 2:30-3:30
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 (non-exhaustive) 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: