Statistics 625 - Regression Modeling

Krista Gile

M W 2:30PM 3:45PM

UMass Amherst
Lederle Grad Res Tower Rm 173
Regression is the most widely used statistical technique. In addition to learning about regression methods this course will also reinforce basic statistical concepts and expose students (for many for the first time) to "statistical thinking" in a broader context. This is primarily an applied statistics course. While models and methods are written out carefully with some basic derivations, the primary focus of the course is on the understanding and presentation of regression models and associated methods, data analysis, interpretation of results, statistical computation and model building. Topics covered include simple and multiple linear regression; correlation; the use of dummy variables; residuals and diagnostics; model building/variable selection, regression models and methods in matrix form; an introduction to weighted least squares, regression with correlated errors and nonlinear including binary) regression.

STATISTC 516 Note: Stat 515 and Stat 516 (or equivalent knowledge) are required for this course.

Permission is required for interchange registration during the add/drop period only.