The Gauss-Markov Theorem states that in a linear regression model, if the errors have an expected value of zero, are uncorrelated, and have constant variance, then the ordinary least squares (OLS) estimator is the best linear unbiased estimator (BLUE) of the coefficients. This theorem connects to key properties of estimators, emphasizing conditions under which OLS estimators achieve optimality in terms of variance.
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