Design an A/B test for a new checkout flow

Last updated: January 19, 2026

Quick Overview

Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.

Oracle
Statistics & Math
Data Scientist
Oracle
January 19, 2026
Data Scientist
Onsite
Statistics & Math
Easy

49

6

3,958 solved


Design an experiment to test the impact of a redesigned homepage. Include sample size calculation, metrics, and analysis plan.

Oracle 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
  • 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
Conditional probability and Bayes theorem
Regression analysis
Bayesian vs frequentist inference
Central Limit Theorem
Confidence intervals and significance levels
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
  • What alternative statistical method could you use here?
  • What if the sample size is very small?
  • How would you design a follow-up experiment based on these results?
  • 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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