Interpret mixed results across segments from an experiment
Last updated: June 1, 2026
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Grubhub
June 1, 202649
4
1,995 solved
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Grubhub values data-driven decision making. This Phone 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
- 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
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 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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Problem Formulation
In this scenario, we are tasked with interpreting mixed results from an experiment conducted by Grubhub across different segments. The aim is to determine if the observed results are statistically sig...
Solution Approach
- Data Collection: Gather data from each segment and ensure that sample sizes are adequate for statistical power.
- Perform Regression Analysis: Use linear or logistic regression to model th...
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