Interpret mixed results across segments from an experiment

Last updated: March 9, 2026

Quick Overview

An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Optiver
Statistics & Math
Data Scientist
Optiver
March 9, 2026
Data Scientist
Phone Screen
Statistics & Math
Medium

18

5

2,137 solved


An experiment shows conflicting results. What conclusions can you draw? What are the caveats?

Optiver 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
  • 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
Power analysis and sample size calculation
Probability distributions
Multiple testing correction (Bonferroni, FDR)
Conditional probability and Bayes theorem
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?
  • How would you explain this result to a non-technical audience?
  • How would you handle multiple comparisons?
  • How would you design a follow-up experiment based on these results?
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