Explain Statistical Outputs to Non-Technical Stakeholders
Overview
This question evaluates a data scientist's competence in interpreting and communicating core statistical outputs—such as confidence intervals, limitations of p-values, distribution visualizations, and the bias–variance trade-off—to non-technical stakeholders during A/B test reviews.
Amazon
Aug 4, 2025, 10:55 AM
Data Scientist
Technical Screen
Statistics & Math
51
0
A/B Test Dashboard Interpretation and Core Statistics Concepts
Scenario
You are reviewing an A/B test dashboard for an experiment (e.g., Variant B vs Control A on conversion rate) and must explain statistical outputs to non-technical stakeholders during a technical phone screen.
Questions
- What is a confidence interval, and how would you interpret it in an experiment report?
- List two shortcomings of relying solely on p-values.
- Compare bar chart, box plot, and violin plot for displaying a distribution; give pros and cons for each.
- Explain the bias–variance trade-off in model evaluation.
Solution
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