ST 452 Applied Regression Analysis

ST
452
Hours
3
Applied Regression Analysis

Data analysis using multiple linear regression, including residual plots, transformations, hypothesis tests, outlier diagnostics, analysis of covariance, variable selection techniques and co-linearity. Logistic regression uses similarly discussed for dealing with binary valued independent variables.

Prerequisite(s):(EN 101or 120) and (EN 102orEN 121orEN 103orEN 104) and (MATH 121orMATH 125orMATH 145) and (EC 110orEC 112) and (EC 111orEC 113) and (AC 210orAC 211) and (LGS 200orLGS 201) andST 260