Linear Models

3 credits · Undergraduate

This course discusses the estimation of parameters in the multiple linear regression model by the least-squares method. Topics covered include the statistical properties of the least-squares estimators, the Gauss-Markov theorem, estimates of residual and regression sums of squares, distribution theory under normality of the observations, assessment of normality, variance stabilizing transformations, examination of multicollinearity, variable selection methods, logistic regression for a binary response, log-linear models for count data, and generalized linear models. Prerequisite(s): One of MATH 150-3 or MATH 220-3; and one of ECON 205-3, MATH 240-3, MATH 371-3, PSYC 315-4, STAT 240-3 or STAT 371-3 Preclusion(s): MATH 471-3, MATH 499-3 when offered as Regression