I.Contents：
Topic1. Review of Basics.
Topic2. Simple and Multiple regression.
Topic3. Problems and Remedies- Normality, unequal variances, correlated errors, outliers and Influential observations, multicollinearity.
Topic4. Variable Selection Procedures.
Topic5. Applications to analysis of variance and covariance.
Topic6. Logistic Regression Analysis.
II.Course prerequisite：
III.Reference material ( textbook(s) )：
Text book: Sen Ashish and Srivastava M. (1990). Regression Analysis: Theory, Methods, and Applications. Springer
References: Rawlings, J. O. Pantula , S. G., and Dickey, D. A. (1998). Applied Regression Analysis: Research Tool. Second Edition. Springer. Rao, C. R. and Toutenburg, H. (1999). Linear Models: Least Squares and Alternatives. Second Edition. Springer.
Kleinbaum, D. G., Kupper, L. L., Muller, K. E., and Nizam, A. (1998). Applied Regression Analysis and other Multirariable Methods. Duxbury.
IV.Grading scheme：
Homework: 20%
Quiz: 20%
Midterm: 30%
Final: 30%
Project: 10%
V.Others：