"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 textbookBasic Econometrics by Damodar N. Gujarati. You can follow the steps and then solve the problem in each exercise. Since this site is still a trial version. Any error or suggestion, please feel free to let me know and I will correct it as soon as possible, thank you.