Logical

Texas Sharpshooter

What it is

Cherry-picking data clusters after the fact to create the appearance of a meaningful pattern — like painting a target around bullet holes.

How it works

Given enough data, random clusters will appear. The Texas Sharpshooter selects these clusters and presents them as evidence of a pattern or cause, ignoring all the data that doesn't fit. This is especially common with health scares, conspiracy theories, and any situation where large datasets can be mined for apparent correlations.

Real-world examples

  • •A cancer cluster near a factory being attributed to the factory without controlling for dozens of other factors.
  • •Investment funds highlighting their best-performing period while ignoring the overall track record.
  • •Conspiracy theorists connecting selected events while ignoring the thousands of events that don't fit.

Ethical guidelines

  • ●Hypotheses should be formed before examining data, not reverse-engineered from it.
  • ●Presenting post-hoc patterns as pre-determined predictions is intellectually fraudulent.
  • ●Any pattern found in data must be tested against new, independent data to be validated.

How to defend against it

  • ►Ask whether the pattern was predicted in advance or discovered after the fact.
  • ►Look for all the data that DOESN'T fit the proposed pattern — not just the data that does.
  • ►Demand independent replication before accepting data-mined patterns as real.

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