The main assumption of OLS for any model is:
A)to check whether the error term is uncorrelated with the response variable.
B)to check whether the error term is correlated with the explanatory variables.
C)to check whether the error term is uncorrelated with the explanatory variables.
D)to check whether the error term is correlated with the response variable.

Question

​The main assumption of OLS for any model is:
A)​to check whether the error term is uncorrelated with the response variable.
B)​to check whether the error term is correlated with the explanatory variables.
C)​to check whether the error term is uncorrelated with the explanatory variables.
D)to check whether the error term is correlated with the response variable.

Quizplus · Accepted Answer

The main assumption of OLS is that the error term is uncorrelated with the explanatory variables. This is because OLS aims to estimate the relationship between the response variable and the explanatory variables by minimizing the sum of squared residuals, which are the differences between the observed values and the predicted values based on the explanatory variables. If the error term is correlated with the explanatory variables, it means that there is still some systematic variation in the response variable that is not captured by the explanatory variables, and this can lead to biased and inconsistent estimates. Therefore, it is important to check the assumption of uncorrelated errors with the explanatory variables when using OLS.

​The Main Assumption of OLS for Any Model Is

The Main Assumption of OLS for Any Model Is