Design an A/B test for a recommendation algorithm
Last updated: July 25, 2025
Quick Overview
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
Dropbox
July 25, 202537
4
3,349 solved
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
This statistics question from Dropbox's Onsite 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
- State the correct formula or theorem with clear definitions
- Apply the concept to the given scenario step by step
- Interpret the result in plain language
- Identify assumptions and when they might be violated
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?
- How would you design a follow-up experiment based on these results?
- What alternative statistical method could you use here?
- What assumptions does this test make, and how would you validate them?
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Problem Formulation
To test the impact of new pricing tiers on user engagement at Dropbox, we will conduct an A/B test. In this experiment, users will be randomly assigned to one of two groups: Group A (control group wit...
Solution Approach
- Define Metrics: The primary metric is the average number of files uploaded per user in a month.
- Sample Size Calculation: To achieve a desired statistical power (commonly 80%) and signifi...
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