Interpret mixed results across segments from an experiment
Last updated: October 26, 2025
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
JPMorgan
October 26, 202592
6
3,926 solved
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
JPMorgan values data-driven decision making. This Technical Screen 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 handle multiple comparisons?
- How would you explain this result to a non-technical audience?
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Browse Statistics QuestionsSample Answer
Problem Formulation
To analyze the mixed results across segments from an experiment conducted by JPMorgan, we need to define our null hypothesis (H0) and alternative hypothesis (H1). Let’s denote the segments as ( S_1, ...
Solution Approach
To analyze the mixed results, we can take the following steps:
- Data Collection: Gather the outcome data for each segment.
- Statistical Test Selection: Use ANOVA (Analysis of Variance) to...
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