= Regression toward the mean
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<Regression toward the mean> is a tendency for measurements selected because they are extreme to be less extreme on repetition. A large first reading can combine a persistent signal with unusually positive <measurement error>; a fresh error need not repeat that contribution. This can change the selected group's <mean> even when the underlying signal stays fixed and no <intervention> occurs.
The claim concerns a <conditional expectation>, not a rule that every individual moves toward the population <mean>. Some second readings are more extreme. Nor does an observed change establish a <causal effect>: selection alone can produce it. The following original <normal distribution> model makes both distinctions quantitative.
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