DSCI 407 - Statistical Modeling and Regression

4 credit(s)
Regression analysis is a powerful applied statistical technique. This course focuses on regression models and associated methods of statistical inference, data analysis, interpretation of results, statistical computation and model building. Topics covered include simple and multiple linear regression; correlation; the use of dummy variables; residuals and diagnostics; model building/variable selection; expressing regression models and methods in matrix form; an introduction to weighted least squares, regression with correlated errors and nonlinear regression. The course makes extensive use of R.
Offered: Alternate years.

Prerequisite(s): MATH 307 with a grade of C or better