Design an A/B test for a search ranking change

Last updated: December 8, 2025

Quick Overview

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

Splunk
Statistics & Math
Data Scientist
Splunk
December 8, 2025
Data Scientist
Technical Screen
Statistics & Math
Hard

162

6

3,539 solved


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

Statistics questions at Splunk test your ability to reason quantitatively and design rigorous experiments. This Technical Screen question evaluates your understanding of statistical inference and its application to business decisions.

What the Interviewer Expects
  • Derive results from first principles when needed
  • Handle complex scenarios with multiple interacting variables
  • Design experiments that account for real-world complications
  • Discuss advanced topics: Bayesian methods, causal inference, resampling
  • Connect statistical concepts to business decision-making
  • Identify subtle errors in reasoning (Simpson's paradox, survivorship bias)
Key Topics to Cover
Hypothesis testing (H0, H1, p-values)
Conditional probability and Bayes theorem
Confidence intervals and significance levels
Power analysis and sample size calculation
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 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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