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)