Interpret no significant difference from an experiment
Last updated: February 2, 2026
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
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An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Reddit values data-driven decision making. This Take-home Project 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
- 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?
- How would you explain this result to a non-technical audience?
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Problem Formulation
To analyze the conflicting results from the experiment conducted by Reddit, we need to formally define our hypothesis testing framework. Let (null hypothesis) be that there is no significant...
Solution Approach
- Data Collection: Start by gathering the outcome variable data from both groups.
- Statistical Test Selection: Choose an appropriate test, such as a t-test for means if the data is normall...
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