Design an A/B test for a recommendation algorithm

Last updated: May 12, 2026

Quick Overview

Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Airbnb
Statistics & Math
Data Scientist
Airbnb
May 12, 2026
Data Scientist
Phone Screen
Statistics & Math
Hard

6

14

2,580 solved


Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Statistics questions at Airbnb test your ability to reason quantitatively and design rigorous experiments. This Phone Screen question evaluates your understanding of statistical inference and its application to business decisions.

What the Interviewer Expects
  • Derive results from first principles when needed
  • Handle complex scenarios with multiple interacting variables
  • Design experiments that account for real-world complications
  • Discuss advanced topics: Bayesian methods, causal inference, resampling
  • Connect statistical concepts to business decision-making
  • Identify subtle errors in reasoning (Simpson's paradox, survivorship bias)
Key Topics to Cover
Multiple testing correction (Bonferroni, FDR)
Confidence intervals and significance levels
Conditional probability and Bayes theorem
Central Limit Theorem
How to Approach This
  1. Define your hypotheses (H0 and H1) clearly before performing any test.
  2. Calculate required sample size BEFORE running an experiment, using power analysis.
  3. Remember the Central Limit Theorem: sample means become approximately normal with large n.
  4. Watch for Simpson's paradox. Always segment data by key dimensions.
  5. Distinguish between statistical significance and practical significance.
Possible Follow-up Questions
  • What if the sample size is very small?
  • How would you handle multiple comparisons?
  • What assumptions does this test make, and how would you validate them?
  • How would you explain this result to a non-technical audience?
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