Design an A/B test for a new checkout flow
Last updated: November 28, 2025
Quick Overview
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
SentinelOne
November 28, 2025221
6
2,942 solved
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Statistics questions at SentinelOne 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
- 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 handle multiple comparisons?
- What assumptions does this test make, and how would you validate them?
- How would you explain this result to a non-technical audience?
- What alternative statistical method could you use here?
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Problem Formulation
To design an A/B test for the new checkout flow on the SentinelOne homepage, we need to set up our hypotheses:
- Null Hypothesis (H0): The redesigned homepage does not lead to a statistically sig...
Solution Approach
- Determine the baseline conversion rate: Let's assume the current conversion rate is 5% (0.05).
- Decide the minimum detectable effect (MDE): We want to detect an increase to at least 6% (0...
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