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Experimentation and causality

Interview question

  • seniorlevel
  • 12 minsuggested time
  • 2Data scientist, Data analyst

A redesigned seat map lifts paid seat selection by 6% in week 1, 3% in week 2 and 2% in week 3. Separately, product complains that tests take too long. How do you interpret the decay, and how would you make tests faster without cutting corners?

Tests: Novelty and learning effects, choosing test duration, long-term vs short-term metrics, and legitimate variance reduction (for example CUPED-style covariate adjustment).

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