Design an A/B Test for Group Video Calls Impact
MetaData Scientist · Technical Screen
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This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Design an A/B Test for Group Video Calls Impact states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Scenario
Instagram plans an A/B experiment to evaluate the impact of group video calls.
Question
Design an end-to-end test: hypothesis, randomization unit, sample size and duration. How do you choose the randomization unit given strong network effects? If clustering is infeasible, what alternative designs mitigate interference? Which statistical tests would you apply to continuous versus proportion metrics? How would you present the experiment results to non-technical PMs versus data-science peers?
Hints
Discuss cluster vs. user-level assignment, geography splits, t-tests vs. z-tests, and storytelling for different audiences.
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