AMT 325 2.0 Regression Analysis – Department of Mathematics

Course: AMT 325 2.0 Regression Analysis (Optional)

Course content:

Introduction to Regression; Applications of regression analysis; Steps in regression analysis; Simple Linear Regression; Parameter estimation; Interpretation of regression coefficients; Properties of least squares estimators; test of hypotheses; Confidence intervals; Predictions; Measuring the quality of fit; Regression line through the origin; Model Adequacy Checking; Residual analysis; Multiple Linear Regression; Matrix notations; Parameter estimation; Interpretation of regression coefficients; Test of hypotheses; Confidence intervals/region; Prediction; Introduction to Multicollineartiy; Qualitative Variables as Predictors; Introduction to Variable Selection Procedures; Form a model using statistical software packages.

Recommended Readings:

1. Montgomery,D.C., Peck,E.A., & Vining, G.G. (2012). Introduction to Linear Regression Analysis (5^th ed).John Wiley & Sons Inc.
2. Kutner,M.H., Li,W., Nachtsheim,C.J. & Neter,J. (2004). Applied Linear Statistical Models. McGraw-Hill.