Stat 7410: Theory of Linear Models

Peter F. Craigmile

Email: pfc <at>
Office: Cockins Hall, Room 427

This is a course on the theory of the linear model, the most commonly used statistical model. As well as providing the theory for the definition, estimation, and testing in this class of models, we consider statistical methods for multiple comparisons, and consider a breakdown in the model assumptions. More advanced topics in this course include the discussion of blocking, random and mixed effects, and an introduction to generalized linear models.

Prerequisites: Stat 6860 (Foundations of the Linear Model), as well as a solid course on linear algebra at the undergraduate level; Stat 6802 (Statistical Theory II), introducing the theory for statistical estimation. Stat 6910 and 6950 (Applied Statistics I and II) giving exposure to analysis of variance and experimental design, as well as regression modeling.

  • This course is hosted on Carmen.

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