Econometrics: Simple Linear Regression (Mistakes to Avoid)

The purpose of this econometrics course is to share with you the confusion points and some of the silly mistakes that students do while studying Simple Linear Regression.

Mistake 1: Placement of error term in population & sample regression equations. Also, have you ever seen 'X hat' in any of the regression equations?

Mistake 2: What is it that we minimise in the method of OLS?
Do you first sum the sample errors and then square the sum?
OR
Do you first square the sample errors and then take the sum?

Mistake 3: Not practicing the mathematical expressions. There are multiple ways of writing the formula for 'B2 hat'. Do you know all of them?

Mistake 4: You must have encountered some assumptions while studying Simple Linear Regression. Do you put the assumptions on the sample error? Also, what is the mathematical expression for the sample error?

Mistake 5: Not paying enough attention to the assumptions and linkages.
Example: What do you think about the following two statements? True or False.
Statement 1: In the presence of heteroscedasticity, the OLS estimators are biased.
Statement 2: For OLS estimators to be BLUE, the population error should follow a normal distribution.

Mistake 6: Standard Deviation OR Standard Errors?

Mistake 7: Testing the hypothesis on estimators or parameters?

So, what are you waiting for? Get started with the course so that you don’t make the same mistakes in your final exam!