What term describes the estimator's quality if it produces the population parameter on average?

An estimator is deemed unbiased if it produces the population parameter on average across numerous samples. This means that if you were to take a large number of random samples from the population and calculate the estimator each time, the average value of the estimates would equal the true population parameter. This property is crucial because it implies that the estimator neither systematically overestimates nor underestimates the parameter, leading to a straightforward interpretation of its results.

While terms like efficient, reliable, and valid have their significance in statistics, they pertain to different properties. For example, efficiency concerns how closely the estimator approximates the parameter with the smallest variance among unbiased estimators, and reliability typically refers to the consistency of an estimator's performance across different situations. Validity relates to how well the estimator measures what it is supposed to measure, but it does not specifically address whether it achieves the true population parameter on average. Thus, unbiased is the term that accurately captures the idea of an estimator mirroring the population parameter over repeated sampling.