Design an A/B test for a search ranking change
Last updated: April 19, 2026
Quick Overview
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
Notion
April 19, 202620
15
825 solved
Design an experiment to test the impact of new pricing tiers. Include sample size calculation, metrics, and analysis plan.
This statistics question from Notion'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 design a follow-up experiment based on these results?
- How would you handle multiple comparisons?
- What alternative statistical method could you use here?
- 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, we will design an A/B test that compares two groups: Group A (control) receiving the existing pricing structure and Group B (treatment) ...
Solution Approach
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Sample Size Calculation: To determine the required sample size for each group, we will use the formula for sample size in A/B testing:
[ n = \frac{(Z_{\alpha/2} + Z_{\beta})^2 \cdot (p_...
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