Explain how CUPED increases statistical power and required data
Tests ANCOVA variance reduction. Answer: CUPED regresses pre-experiment X on Y, shrinking variance by (1-ρ²); needs pre-randomization prognostic baseline; beats difference scores. Red flag: calling it Y-X subtraction or saying it changes the effect.
WHAT IT TESTS: Your grasp of regression-based covariate adjustment versus naive baseline subtraction. ANSWER OUTLINE: Define CUPED as ANCOVA at scale; explain it regresses pre-experiment X on post-experiment Y, yielding variance ~(1-ρ²)σ²; list requirements (pre-randomization, prognostic baseline); contrast with difference scores (variance 2σ²(1-ρ), only better if ρ>0.5); note CUPED is never worse than unadjusted and optimal at any ρ.
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