This course introduces regression analysis using matrix algebra. Topics include bivariate regression, multivariate regression, tests of significance, regression diagnostics, indicator variables, interaction terms, extra sum of squares, and the general linear model. Other topics may be addressed such as logistic regression and path analysis. Statistical programming software may be used.
Average rating: 4.00
Average GPA: 3.82 between 76 students
"W"s are considered to be 0.0 quality points. "Other" grades are not factored into the average GPA calculation.