"When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a very meagre and unsatisfactory kind."

Part 1: Single-Equation Regression Models

1. The Nature of Regression Models
2. Two-Variable Regression Analysis: Some Basic Ideas
3. Two-Varibale Regression Model: The Problem of Estimation
4. The Normality Assumptions: Classical Normal Linear Regression Model (CNLRM)
5. Two-Variable Regression:Interval Estimation and Hypothesis Testing
6. Extensions of the Two-Variable Linear Regression Model
7. Multiple Regression Analysis:The Problem of Estimation
8. Multiple Regression Analysis:The Problem of Inference

Part 2: Relaxing the Assumptions of the Classical Model

9. Multicollinearity and Micronumerosity
10. Heteroscedasticity
11. Autocorrelatio



Part 3: Topics in Econometrics

12. Regression on Dummy Variables

This is a simple step-by-step solution demonstration supplementary to the textbook Basic Econometrics by Damodar N. Gujarati. Students can follow the steps and solve the problem in each selected exercise question. Please feel free to give your comments and suggestions to improve this page. Thank you.