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
May 12, 20266
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
How to Approach This
- Define your hypotheses (H0 and H1) clearly before performing any test.
- Calculate required sample size BEFORE running an experiment, using power analysis.
- Remember the Central Limit Theorem: sample means become approximately normal with large n.
- Watch for Simpson's paradox. Always segment data by key dimensions.
- 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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Browse Statistics QuestionsSample Answer
Problem Formulation
To design an A/B test for the impact of new pricing tiers on Airbnb's recommendation algorithm, we must first define our objectives. We want to measure how the introduction of new pricing tiers affect...
Solution Approach
We will conduct a randomized controlled trial (RCT) with two groups: the control group (existing pricing tiers) and the treatment group (new pricing tiers). The following steps outline the approach:
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