Interpret no significant difference from an experiment
Last updated: September 30, 2025
Quick Overview
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Coinbase
September 30, 2025595
5
2,447 solved
An experiment shows conflicting results. What conclusions can you draw? What are the caveats?
Coinbase asks this during the Take-home Project to assess your experimentation skills. They want to see how you define success metrics, design controlled experiments, and interpret results with appropriate statistical rigor.
What the Interviewer Expects
- Design a rigorous experiment with proper randomization and sample size calculation
- Define primary and guardrail metrics with clear rationale
- Address novelty effects, network effects, and interference
- Segment results appropriately and identify heterogeneous treatment effects
- Propose follow-up analyses when results are ambiguous
Key Topics to Cover
How to Approach This
- Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
- Run experiments long enough to account for novelty effects and weekly seasonality.
- Use funnel analysis to identify where users drop off for maximum optimization impact.
- Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
- Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
- What if you discover a bug in the logging during the experiment?
- How would you handle interference between treatment and control?
- What would you do if a stakeholder wants to end the experiment early because initial results look good?
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Browse Analytics QuestionsSample Answer
Problem Setup
In this scenario, we need to analyze the results from an A/B test conducted by Coinbase to determine if there is a significant difference between the control and treatment groups. The primary analytic...
Methodology
To assess whether there is no significant difference between the groups, we will conduct a two-sample t-test (or a non-parametric equivalent if the data is not normally distributed) to compare the mea...
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