Interpret mixed results across segments from an experiment
Last updated: February 26, 2026
Quick Overview
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
Jane Street
February 26, 202628
5
2,451 solved
An experiment shows a 3% lift with p=0.08. What conclusions can you draw? What are the caveats?
This statistics question from Jane Street's Technical Screen 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
- 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
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 assumptions does this test make, and how would you validate them?
- What if the sample size is very small?
- How would you design a follow-up experiment based on these results?
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Browse Statistics QuestionsSample Answer
Problem Formulation
We are given an experiment that yields a 3% lift with a p-value of 0.08. To analyze this, we need to set up the null and alternative hypotheses:
- Null Hypothesis (H0): There is no effect (the li...
Solution Approach
To interpret the results, we need to assess the significance level (commonly set at 0.05) compared to our p-value. Since 0.08 > 0.05, we do not reject H0 at the conventional significance level. Here's...
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