Simple Linear Model including assumptions, estimation, model diagnostics, transformations and tests. Multiple Regression Models: matrix formulation and analysis including estimation and tests of assumptions, outliers and measures of influence. Variable selection. Analysis of Variance including models with indicator variables.
