Calculate variance for coin flips

Last updated: July 1, 2025

Quick Overview

Given the following scenario about user conversion, calculate the the sample size needed.

Dropbox
Analytics & Experimentation
Data Scientist
Dropbox
July 1, 2025
Data Scientist
Take-home Project
Analytics & Experimentation
Hard

3

0

462 solved


Given the following scenario about user conversion, calculate the the sample size needed.

Dropbox 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 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
Sample size and power calculation
A/B testing methodology
Segmentation and heterogeneous effects
Metric definition and success criteria
Simpson's paradox and ecological fallacy
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
  • What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
  • What if you discover a bug in the logging during the experiment?
  • What would you do if a stakeholder wants to end the experiment early because initial results look good?
  • How would you handle interference between treatment and control?
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