Problem
Scenario
You work on a consumer product team running an A/B test for a small UI change on a high-traffic surface. The experiment shows a statistically significant lift, but the estimated effect size is very small and close to the noise floor. Your team is unsure whether to trust the result enough to ship.
Question
How would you decide whether to trust an experiment result when the observed effect size is small? What evidence would you look for before recommending ship, don’t ship, or rerun?
What matters
- Statistical significance vs practical significance
- Confidence interval width and overlap with meaningful effect sizes
- Power and whether the test was designed for such a small lift
- Experiment validity checks such as SRM and peeking risk
- Guardrail performance before shipping
Practicing as: Product Growth Analyst interview at QuoraHi, I'll play your Quora interviewer for the Product Growth Analyst role. Candidates describe these interviews as mixed and moderately difficult, so expect me to be professional and fair. Take your time with the question above and answer like we're in the room.
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