Answer-In a simple linear regression model Y = β0 + β1X + u, the Ordinary Least Squares (OLS) est...

The core principle of OLS estimation is to choose 0hat and 1hat such that they minimize the Sum of Squared Residuals SSR, uihat. This property, under the Gauss-Markov assumptions, makes OLS the Best Linear Unbiased Estimator BLUE.

Question

In a simple linear regression model Y = β0 + β1X + u, the Ordinary Least Squares (OL

S estimator is "best" because it:

A Minimizes the sum of the residuals.

B Minimizes the sum of the absolute residuals.

C Minimizes the sum of the squared residuals.

D Maximizes the R-squared value.

E Ensures residuals sum to zero.

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In a simple linear regression model Y = β0 + β1X + u, the Ordinary Least Squares (OL

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