Interpret mixed results across segments from an experiment

Last updated: May 15, 2026

Quick Overview

An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?

Two Sigma
Statistics & Math
Data Scientist
Two Sigma
May 15, 2026
Data Scientist
Take-home Project
Statistics & Math
Easy

148

9

4,522 solved


An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?

This statistics question from Two Sigma's Take-home Project 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
Central Limit Theorem
Conditional probability and Bayes theorem
Regression analysis
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
  • What if the sample size is very small?
  • What alternative statistical method could you use here?
  • How would you explain this result to a non-technical audience?
  • 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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