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unbiasedness, efficiency, and consistency. An estimator is unbiased if its expected value is the true value of the parameter; it is consistent if it converges to the true value as the sample size gets larger, and it is efficient if the estimator has a lower standard error than other unbiased estimators for a given sample size. Ordinary least squares

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