Minimum variance refers to the property of an estimator that aims to produce the lowest possible variance among all estimators. This characteristic is crucial for ensuring that the estimators are not only unbiased but also efficient, providing reliable estimates that have the least spread or uncertainty. By achieving minimum variance, estimators can be considered optimal in terms of their precision and reliability, linking them closely to concepts such as best linear unbiased estimators, overall efficiency in statistical inference, and asymptotic properties as sample sizes grow.
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