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    Question

    In a simple linear regression model Y = β0 + β1X + u,

    the Ordinary Least Squares (OLS) estimator is "best" because it:
    A Minimizes the sum of the residuals. Correct Answer Incorrect Answer
    B Minimizes the sum of the absolute residuals. Correct Answer Incorrect Answer
    C Minimizes the sum of the squared residuals. Correct Answer Incorrect Answer
    D Maximizes the R-squared value. Correct Answer Incorrect Answer
    E Ensures residuals sum to zero. Correct Answer Incorrect Answer

    Solution

    The core principle of OLS estimation is to choose β0_hat and β1_hat such that they minimize the Sum of Squared Residuals (SSR), Σ(u_i_hat)². This property, under the Gauss-Markov assumptions, makes OLS the Best Linear Unbiased Estimator (BLUE).

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