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
Statistics & Math
Data Scientist
Dropbox
July 25, 2025
Data Scientist
Onsite
Statistics & Math
Easy

37

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
Confidence intervals and significance levels
Probability distributions
Bayesian vs frequentist inference
Regression analysis
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
  • 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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Sample 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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