Regression to the Mean

Extreme outcomes tend to be followed by more average ones, simply because chance contributed to the extreme. No cause is needed; the pattern is statistical.

Why it Matters

People invent causal stories for what is just regression, crediting or blaming interventions that did nothing. It underlies illusory treatment effects and explains why punishment seems to work and praise seems to backfire.

Signals

• An intervention applied right after an extreme, then improvement credited to the intervention.
• "Praise made them worse, criticism made them better."
• Superstitious cause drawn from a single extreme event.

Benefits

Recognizing it prevents false causal claims and demands controls and base rates before crediting a fix.

Risks

Attributing regression to a cause; building policy on an effect that was never real.

Tensions

The mind insists on causes, but many sequences are governed by chance plus regression, not by the story.

Examples

A star performer's "off year" after a record one; a treatment that "works" because it was tried when symptoms were at their worst.