MA 5013 Applied Regression Analysis

Course Details

Unit I: Simple linear regression, multiple linear regression, model adequacy checking, transformations and weighting to correct model inadequacies.
Unit II: Polynomial regression models, orthogonal polynomials. dummy variables, variable selection and model building, multicollinearity.
Unit III: : Nonlinear regression. Generalized linear models, autocorrelation, measurement errors, calibration problem, bootstrapping.

Course References:

Text Books:
1. 1. Montgomery, D. C., Peck, E. A., and Vining, G. (2012), Introduction to Linear Regression Analysis (5th ed.), Hoboken, NJ: Wiley.
1. Draper, N. R., and Smith, H. (2003), Applied Regression Analysis, New York: Wiley.
2. Sen, A. A. and Srivastava, M. (1990). Regression Analysis Theory, Methods & Applications, Springer-Verlag, Berlin.
3. Bowerman, B. L. and O'Connell, R. T. (1990). Linear Statistical Models: An Applied Approach, PWS-KENT Pub., Boston.