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1. Introduction to Regression Models.
2.Simple Linear Regression.
3.A Review of Matrix Algebra and Important Results of Random Vectors.
4.Multiple Linear Regression Model.
5.Specification Issues in Regression Models.
6.Model Checking.
7.Model Selection.
8.Case Studies in Linear Regression.
9.Nonlinear Regression Models.
10.Regression Models for Time Series Situations.
11.Logistic Regression.
12.Generalized Linear Models and Poisson Regression. Brief Answers to Selected Exercises. Statistical Tables. References.
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