Description
This course introduces methods for fitting and interpreting regression models. Topics include ordinary least squares, inference for the normal regression model, model diagnostics and test of fit, transformation of data, qualitative predictors, effects of measurement error, and model selection. Prerequisite: MATH 210, MATH 216, and MATH 209