Average view duration is a ratio — why can't you just t-test it?

Variance & ratio metricsHard

Problem. You want to compare average view duration (AVD = total watch time ÷ total views) between two arms, randomized by user. A teammate computes AVD per arm and runs a standard two-sample t-test. Why is that variance estimate wrong, and what do you do instead?

Before you reveal: say your answer out loud, as if you were in the real interview — get your reasoning across clearly first. There is no single correct answer: reading what the interviewer is really after and defending your own thinking is what makes an answer strong.

Interview tips

Strong-answer signal: recognizing AVD as a ratio with a user-level randomization unit, and using the delta method (or user-level bootstrap / clustered variance) instead of a per-view t-test. Common trap: running a standard t-test on per-view data, treating correlated within-user views as independent and understating the variance.

A/B Test & Causal Inference Questions0 / 220