Course Description
This course will introduce many methods that are commonly used in applications. Examples include: model generation, selection, assessment, and diagnostics in the context of multiple linear regression (including penalized regression); linear mixed models; generalized linear models; generalized linear mixed models; nonparametric regression and smoothing; and finite-population sampling basics. Coverage will include some theory, plus implementation using SAS and/or R.
Spring 2024
Instructors
Meeting Patterns
Classes Start:
January 8, 2024
Classes End:
April 23, 2024
Location:
00322 111 Lampe Drive
Class Days:
M W
Class Start Time:
3:00pm
Class End Time:
4:15pm
Class Type:
Lecture
Credits:
3.00
Restrictions:
Prerequisite:ST 703; Corequisites: ST 702 and ST 705
