Explain multiple testing correction with an example

Last updated: October 6, 2025

Quick Overview

Explain multiple testing correction in simple terms and provide a concrete example.

Stripe
Analytics & Experimentation
Data Scientist
Stripe
October 6, 2025
Data Scientist
Take-home Project
Analytics & Experimentation
Hard

128

4

3,667 solved


Explain multiple testing correction in simple terms and provide a concrete example.

Analytics questions at Stripe evaluate your ability to define metrics, design experiments, and derive actionable insights from data. This Take-home Project question tests your end-to-end analytical thinking.

What the Interviewer Expects
  • Design complex experimentation strategies for tricky scenarios
  • Handle multi-armed bandits, switchback experiments, and quasi-experiments
  • Address long-term effects vs short-term metrics
  • Propose causal inference methods when randomization is not possible
  • Build a measurement framework that connects metrics to business value
  • Discuss organizational experimentation culture and maturity
Key Topics to Cover
Guardrail metrics
Long-term vs short-term metrics
Simpson's paradox and ecological fallacy
Sample size and power calculation
A/B testing methodology
How to Approach This
  1. Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
  2. Run experiments long enough to account for novelty effects and weekly seasonality.
  3. Use funnel analysis to identify where users drop off for maximum optimization impact.
  4. Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
  5. Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
  • How would you handle seasonality in your experiment?
  • What if you discover a bug in the logging during the experiment?
  • How would you handle interference between treatment and control?
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