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CRO Glossary

Regression to the Mean

The tendency for extreme early results in a test to move closer to average as more data comes in.

Regression to the mean describes why a variant that looks like a huge winner (or loser) in the first day or two of a test often becomes much less dramatic — or disappears entirely — as the sample grows. Early results are based on small samples and are disproportionately influenced by a few unusual visitors or random noise.

This is a major reason the peeking problem is dangerous: stopping a test early because you see a stunning 40% lift often means you've caught a temporary extreme that will regress toward a much smaller, or nonexistent, effect once more data arrives.

A good practical rule: treat any early result, especially a dramatically positive one, with suspicion until the test reaches its pre-calculated sample size based on the minimum detectable effect (MDE). If a result still holds at full sample size, it's far more trustworthy than a similar-looking result seen on day one.

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