Week - 1 |
Conditional Expectation and Regression |
Week - 2 |
Ordinary Least Squares (LSM) Estimators with Simple Linear Regression Models and Parameters |
Week - 3 |
Assumptions of Linear Regression; Properties of the OLS Estimators |
Week - 4 |
Gauss-Markov Theorem |
Week - 5 |
Hypothesis Testing and Confidence Intervals in Simple Linear Regression |
Week - 6 |
Coefficient of Determination |
Week - 7 |
Multiple Linear Regression Model in Matrix Notation |
Week - 8 |
Hypothesis Testing and Confidence Intervals in Multiple Linear Regression |
Week - 9 |
Dummy Variable |
Week - 10 |
Checking of Assumptions (Residual Analysis) |
Week - 11 |
Multicollinearity |
Week - 12 |
Selection of variable |
Week - 13 |
Heteroscedasticity and Autocorrelation |
Week - 14 |
Applications |