Analysis of the multiple regression model by least squares; statistical properties of the least square analysis, including estimation of error; residual and regression sums of squares; distribution theory under normality of the observations; confidence regions and intervals; tests for normality; variance stabilizing transformations, multicolinearity, variable search methods.
Priority is given to students enrolled in Applied Statistics Specialist or Major programs and Mathematical Sciences - Major: Applied Mathematics program.
