Final answer:
The unbiased estimator with the smaller variance is said to be more efficient, offering more reliability in statistical estimation.
Step-by-step explanation:
The unbiased estimator with the smaller variance is said to be more efficient, offering more reliability in statistical estimation. If there are two unbiased estimators of a population parameter, the one whose variance is smaller is said to be more efficient. In the context of statistical estimation, efficiency relates to the variance of the estimator. A smaller variance among unbiased estimators means that the estimates produced are more consistently closer to the population parameter. Therefore, when comparing two unbiased estimators, the one with the smaller variance is preferable because it offers more reliability. This principle is an element of what is known as the Gauss-Markov theorem, which states that among all linear unbiased estimators, the one with the least variance is considered the best, or most efficient.