Multiple linear regression model including parameter estimation, simultaneous confidence intervals and general linear hypothesis testing using matrix algebra. Applications to forecasting. Residual analysis and outliers. Model selection: best regression, stepwise regression algorithms. Transformation of variables and non-linear regression. Computer analysis of practical real world data.
This course may not be repeated for credit.Syllabus

Sections

This course will be offered next in Fall 2013.