Design an A/B test for a search ranking change
Last updated: August 14, 2025
Quick Overview
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
Meta
August 14, 2025151
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2,394 solved
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
This statistics question from Meta's Phone Screen tests your ability to apply mathematical reasoning to practical problems. The interviewer expects precise definitions, correct methodology, and awareness of assumptions and limitations.
What the Interviewer Expects
- Set up the problem formally with proper notation
- Apply the correct statistical test with clear justification
- Interpret results with appropriate caveats and confidence levels
- Discuss practical significance vs statistical significance
- Identify potential confounders and how to address them
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
- How would you handle multiple comparisons?
- What if the sample size is very small?
- What assumptions does this test make, and how would you validate them?
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Browse Statistics QuestionsSample Answer
Problem Formulation
To evaluate the impact of new pricing tiers on user engagement and revenue, we will conduct an A/B test. We define two groups:
- Control Group (A): Users under the current pricing tiers.
- **Treat...
Solution Approach
We will perform the following steps:
- Sample Size Calculation: We need to determine the sample size that ensures adequate power (e.g., 80%) to detect a meaningful effect size.
- **Random Assign...
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