STAT 5503

Linear Models

0.5 credit · Graduate

Theory of non full rank linear models; estimable functions, best linear unbiased estimators, hypotheses testing, confidence regions; multi-way classifications; analysis of covariance; variance component models; maximum likelihood estimation, Minque, Anova methods; miscellaneous topics.

2021

Readings

Monahan, John F., A Primer on Linear Models, Chapman & Hall/CRC, London 2008 Reference Books: Seber, George A.F. and Lee, Alan J., Linear Regression Analysis, 2nd ed., Wiley, Dan-

Prerequisites & course information

Prerequisite(s): STAT 5600 or permission of the School.

Sources

Course catalogue ↗2026–2027
STAT 5503F F21 ↗2021