A rigorous development of the general linear model, using vector space theory. Generalized inverses, orthogonal projections, quadratic forms, Gauss-Markov theorem, estimability. Weekly hours: 3 Lecture hours and 1 Seminar/Discussion hoursPrerequisite(s): An undergraduate course in mathematical statistics (STAT 342), linear algebra (MATH 266), and STAT 344 or 345.
A rigorous development of the general linear model, using vector space theory. Generalized inverses, orthogonal projections, quadratic forms, Gauss-Markov theorem, estimability. Weekly hours: 3 Lecture hours and 1 Seminar/Discussion hoursPrerequisite(s): An undergraduate course in mathematical statistics (STAT 342), linear algebra (MATH 266), and STAT 344 or 345.
