3. (a) Explain each assumption needed for the OLS estimators in a multiple linear regression model...

 

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3. (a) Explain each assumption needed for the OLS estimators in a multiple linear regression model to be unbiased. (8 pts.) (b) Explain each assumption needed for the OLS estimators in a multiple linear regression model to be BLUE. You may reference part (a) if some of the same assumptions are used instead of explaining them again but be sure to specify which ones are useful here. (3 pts.) (c) For inference, why can we forgo MLR. 6 (normality assumption) when we have large samples? (4 pts.) 3. (a) Explain each assumption needed for the OLS estimators in a multiple linear regression model to be unbiased. (8 pts.) (b) Explain each assumption needed for the OLS estimators in a multiple linear regression model to be BLUE. You may reference part (a) if some of the same assumptions are used instead of explaining them again but be sure to specify which ones are useful here. (3 pts.) (c) For inference, why can we forgo MLR. 6 (normality assumption) when we have large samples? (4 pts.)

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a Assumptions for OLS Estimators to be Unbiased Linearity The relationship between the independent variables and the dependent variable is linear in t... View the full answer