Course Description
Theory of estimation and testing in full and non-full rank linear models. Normal theory distributional properties. Least squares principle and the Gauss-Markoff theorem. Estimability and properties of best linear unbiased estimators. General linear hypothesis. Application of dummy variable methods to elementary classification models for balanced and unbalanced data. Analysis of covariance. Variance components estimation for balanced data.
Non-Std Tm
Through Spring 2025
Spring 2025
Instructors
Meeting Patterns
Classes Start:
January 6, 2025
Classes End:
April 22, 2025
Location:
05270 SAS Hall
Class Days:
M
Class Start Time:
10:40am
Class End Time:
11:30am
Class Type:
Laboratory
Credits:
0.00
Restrictions:
Corequisite: ST 702
