Design an A/B test for a recommendation algorithm
Last updated: July 24, 2025
Quick Overview
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Figma
July 24, 2025167
6
3,800 solved
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Statistics questions at Figma test your ability to reason quantitatively and design rigorous experiments. This Technical Screen question evaluates your understanding of statistical inference and its application to business decisions.
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 explain this result to a non-technical audience?
- What assumptions does this test make, and how would you validate them?
- What if the sample size is very small?
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Browse Statistics QuestionsSample Answer
Setting Up the Problem
Start by formalizing the problem: 1. **Define the hypotheses**: H0 (null hypothesis) and H1 (alternative). Be precise about what you're testing. 2. ...
Solution Approach
**Compute the test statistic**: Apply the appropriate formula using the sample data. **Find the p-value**: The probability of observing a result this...
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