No. 238 · Evidence · Statistics and Probability
Regression to the Mean
Extreme results tend to be followed by ordinary ones, because luck rarely repeats itself.
In the Almanac
“The triumph of mediocrity”, 1933 · “DocuSign”, 2021–2022
Both stories in full, three ways to use it and where it misleads.
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Questions
What is Regression to the Mean?
Regression to the Mean explains why unusually good or bad results tend to be followed by more ordinary ones. In 1933 Horace Secrist wrote a book claiming business was sliding into mediocrity, but it was just this effect. DocuSign's pandemic surge also faded as normal life returned.
How do you use Regression to the Mean?
Before praising, blaming, investing or changing course after an extreme result, ask what would have happened anyway. Look at long track records, not single standout moments, and wait for enough data to spot a real shift.
When does Regression to the Mean matter?
Regression to the Mean is one of the 68 mental models for evidence, the situations where you ask: Is this really true? Within that, it belongs to “Reading the numbers”, alongside Base Rate Fallacy, Bayes’ Theorem and Central Limit Theorem.
What is an example of Regression to the Mean?
Two stories show it at work: The triumph of mediocrity (1933) and DocuSign (2021–2022). Both are told in full in The Mental Models Daily Almanac, which has two stories for each of its 365 models.
Which mental models are related to Regression to the Mean?
Regression Fallacy, Gambler’s Fallacy and Hot-Hand Fallacy. Regression to the Mean itself comes from statistics and probability.