Design an A/B test for a recommendation algorithm

Last updated: November 26, 2025

Quick Overview

Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Snowflake
Statistics & Math
Data Scientist
Snowflake
November 26, 2025
Data Scientist
Onsite
Statistics & Math
Medium

7

10

1,889 solved


Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.

Statistics questions at Snowflake test your ability to reason quantitatively and design rigorous experiments. This Onsite 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
Central Limit Theorem
Confidence intervals and significance levels
Multiple testing correction (Bonferroni, FDR)
Probability distributions
Power analysis and sample size calculation
Causal inference basics
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 handle multiple comparisons?
  • How would you design a follow-up experiment based on these results?
  • What if the sample size is very small?
  • What alternative statistical method could you use here?
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Sample Answer
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