Introduction to Regression Analysis

Catalog description

A course including such topics as simple linear regression: the error model, algebraic derivation of least square estimators, estimating confidence intervals, hypothesis testing, the ANOVA approach to testing, assessing model validity, transformations, residual plots; multiple regression: the general linear model, least square estimation, prediction, residuals; and Logistic regression.