STAT 6120

Linear Models

Course Description

Pre-Requisite(s): Graduate standing in Statistics, or instructor permission

Course develops fundamental methodology to regression and linear-models analysis in general. Topics include model fitting and inference, partial and sequential testing, variable selection, transformations, diagnostics for influential observations, multicollinearity, and regression in nonstandard settings. Conceptual discussion in lectures is supplemented withhands-on practice in applied data-analysis tasks using SAS or R statistical software.


Looks like this course isn't being taught this semester.

Sort by "All" in the top right to see previous semesters.