Definition and Galton's Discovery
Regression to the mean is a statistical phenomenon where an extreme measurement tends to be followed by one closer to the average. In 1886, Francis Galton analyzed parent-child height data and found that tall parents' children were not as tall, and short parents' children were not as short. This observation gave the statistical term "regression" its name.
How It Creates Illusions of Causation
Regression to the mean easily generates false causal beliefs. If a student performs extremely poorly and is scolded, then improves next time, the improvement is attributed to the scolding. In reality, the score would likely have moved toward the average regardless of intervention.
Similarly, praising someone after an exceptional performance followed by a decline leads to the misconception that praise causes complacency. Properly evaluating interventions requires controlled experiments that account for regression to the mean.
Sports Examples
The "Sports Illustrated cover jinx," where athletes featured on the cover often decline the following season, is a textbook case of regression to the mean. Being selected for the cover reflects an unusually strong performance period, and returning to normal levels afterward is a statistical inevitability, not a curse.
Ranking Fluctuations and Regression
If you achieve a temporarily high ranking on MyRank, a subsequent drop does not necessarily mean your ability has declined. It may simply reflect measurement variability and regression to the mean. To identify your true position, referencing the average of multiple measurements rather than a single result is the statistically sound approach.