Regression toward the mean is the tendency for units selected because of an extreme noisy measurement to have less extreme subsequent measurements even without an intervention. It follows because the selection captures both a persistent component and an unusually extreme error component.
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Regression toward the mean is a statistical phenomenon that occurs when extreme values or measurements in a dataset tend to be closer to the average on subsequent measurements or observations. This concept is rooted in the idea that extreme events or behaviors are often influenced by a variety of factors, some of which may be random. As a result, when a measurement is taken that is significantly above or below the average, subsequent measurements are likely to be less extreme and move closer to the mean.