STAT 713 - Applied Linear Statistical Models

Matrix-based regression and analysis of variance procedures at a mathematical level appropriate for a first-year graduate statistics major. Topics include simple linear regression, linear models in matrix form, multiple linear regression, model building and diagnostics, analysis of covariance, multiple comparison methods, contrasts, multifactor studies, blocking, subsampling, and split-plot designs.

Credits: (4)

Requisites:
Pr.: Prior knowledge of matrix or linear algebra and one prior course in statistics. A student may not receive credit for both the STAT 704/705 sequence and STAT 713.

When Offered:
Fall

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Kansas State University

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STAT 713 - Applied Linear Statistical Models