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Experiment hygiene: trust checks before reading results

Before trusting a result: check the sample ratio, run A/A tests, treat surprising wins as likely bugs, never stop a fixed-horizon test at the first p < 0.05, and run at least one full week (ideally two) to cover weekly cycles and novelty or change-aversion effects. Pre-register the metric, the horizon and the decision rule.

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Plain label: trustworthy A/B testing checklistAlso known as: SRM, sample ratio mismatch, A/A test, Twyman's law, peeking, novelty effect

  • Sample ratio mismatch. A chi-square check that the observed split matches the design. About 6% of Microsoft tests had one, and it usually invalidates the result Evidence grade A. Robust evidence: replicated, peer-reviewed research..
  • A/A tests. About 5% should be significant at alpha 0.05; more means a broken pipeline.
  • Twyman's law. A result that looks surprisingly good is probably a bug: re-check before celebrating.
  • No peeking. Checking a fixed-horizon test repeatedly and stopping at the first significant read can multiply false positives about fivefold. Use a fixed horizon or a valid sequential method, and remember that early-stopped estimates run high Evidence grade A. Robust evidence: replicated, peer-reviewed research..
  • Duration. At least one full weekly cycle, preferably two. Novelty bumps and change-aversion dips usually change the size of an effect, not its direction.
  • Before the horizon, only exposure and the sample ratio are shown.

Sources

Source IDs: F26

Book content is paraphrased, never quoted at length. Last verified October 24, 2026.

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