This theorem states that in a linear regression model where the errors have zero mean, are uncorrelated, and have constant variance (homoscedasticity), the ordinary least squares (OLS) estimator is the Best Linear Unbiased Estimator (BLUE). ‘Best’ means it has the minimum variance among all linear unbiased estimators of the regression coefficients, making it the most precise.











