¸£Àû±ÆÕ¾

Estimation and testing in full and non-full rank linear models. Normal theory distributional properties. Least squares principle and the Gauss-Markov theorem. Estimability, analysis of variance and co variance in a unified manner. Practical model-building in linear regression including residual analysis, regression diagnostics, and variable selection. Emphasis on use of the computer to apply methods with data sets. Credit not given for both ³§°ÕÌý705 and ³§°ÕÌý503. Note: this course will be offered in person (Spring) and online (Summer).

P: ³§°ÕÌý501 and ²Ñ´¡Ìý405 or equivalent (Linear Algebra); C: ³§°ÕÌý502

Typically offered in Spring and Summer