Design an A/B test for a new checkout flow
Last updated: August 1, 2025
Quick Overview
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Brex
August 1, 2025130
5
3,072 solved
Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.
Brex values data-driven decision making. This Onsite question assesses whether you can design experiments, interpret results correctly, and avoid common statistical pitfalls like p-hacking or Simpson's paradox.
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
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
- What alternative statistical method could you use here?
- How would you design a follow-up experiment based on these results?
- What if the sample size is very small?
Sharpen Your Skills on Codemia
Practice similar problems with our interactive workspace, get AI feedback, and track your progress.
Browse Statistics QuestionsSample Answer
Problem Formulation
To evaluate the impact of a redesigned homepage on user engagement during the checkout process, we define the following hypotheses:
- Null Hypothesis (H0): There is no difference in the conversio...
Solution Approach
-
Sample Size Calculation: We need to determine the sample size required to detect a statistically significant difference in conversion rates. Using the following formula:
[ n = \frac{(Z_...
Submit Your Answer
