An unbiased estimator is a statistical estimator that, on average, accurately estimates a population parameter. This means that if you were to take many samples and compute the estimator for each, the average of those estimates would equal the true value of the parameter being estimated. This concept is crucial when considering sampling methods and the Central Limit Theorem, as it ensures that estimations made from sample data are reliable and valid reflections of the entire population.
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