1. Introduction to Econometrics
- Definition and Scope 
- What is econometrics?
 - Relationship between econometrics, economics, and statistics.
 
 - Methodology 
- Steps in econometric analysis: formulation, estimation, inference, interpretation.
 - Types of econometric models: cross-sectional, time series, panel data.
 
 
2. Simple Linear Regression Analysis
- Simple Linear Regression Model 
- Formulation and assumptions.
 - Interpretation of the regression equation: intercept, slope.
 
 - Estimation 
- Method of Ordinary Least Squares (OLS).
 - Properties of OLS estimators: unbiasedness, consistency, efficiency.
 
 - Inference 
- Hypothesis testing: significance of coefficients.
 - Confidence intervals.
 
 
3. Multiple Linear Regression Analysis
- Multiple Linear Regression Model 
- Including multiple explanatory variables.
 - Interpretation of coefficients.
 
 - Model Specification 
- Testing model specification: omitted variable bias, functional form.
 
 - Goodness-of-Fit 
- R-squared, adjusted R-squared.
 - F-test for overall significance.
 
 - Each unit can be covered in 10 to 12 hours.
 - Requires good listening and home work
 - can be conducted as tution also
 - Basic statistics on request will be taught (seperate course)
 - Mathematical economics will also be taught on request basis(seperate course)
 - Charges are seperate for each course
 - Can contact via urban pro
 - Crashwork course in 2months can be completed (15 hours each month, cost is 18,000 per month) (If requested this crash course is also possible)