Linear Statistical Models

Theory and practice of linear regression, analysis of variance (ANOVA) and their extensions, including testing, estimation, confidence interval procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. The theory will be approached mainly from the frequentist perspective and use of the computer (mostly R) to analyze data will be emphasized. Prerequisite: CSE 131, Math 309, ((Math 3200 or Math 493) or Math 3211). Math 493 can be taken concurrently. Or permission of instructor.
Course Attributes: FA NSM; AR NSM; AS NSM

Linear Statistical Models

MATHEMATICS AND STATISTICS 439

Section 01

Section 02