Calculate expected value for user retention

Last updated: December 31, 2025

Quick Overview

Given the following scenario about user conversion, calculate the the p-value.

Stripe
Statistics & Math
Data Scientist
Stripe
December 31, 2025
Data Scientist
Technical Screen
Statistics & Math
Hard

50

6

3,949 solved


Given the following scenario about user conversion, calculate the the p-value.

Stripe values data-driven decision making. This Technical Screen 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
  • Derive results from first principles when needed
  • Handle complex scenarios with multiple interacting variables
  • Design experiments that account for real-world complications
  • Discuss advanced topics: Bayesian methods, causal inference, resampling
  • Connect statistical concepts to business decision-making
  • Identify subtle errors in reasoning (Simpson's paradox, survivorship bias)
Key Topics to Cover
Power analysis and sample size calculation
Causal inference basics
Hypothesis testing (H0, H1, p-values)
Bayesian vs frequentist inference
Central Limit Theorem
How to Approach This
  1. Define your hypotheses (H0 and H1) clearly before performing any test.
  2. Calculate required sample size BEFORE running an experiment, using power analysis.
  3. Remember the Central Limit Theorem: sample means become approximately normal with large n.
  4. Watch for Simpson's paradox. Always segment data by key dimensions.
  5. Distinguish between statistical significance and practical significance.
Possible Follow-up Questions
  • What alternative statistical method could you use here?
  • What assumptions does this test make, and how would you validate them?
  • How would you handle multiple comparisons?
  • How would you explain this result to a non-technical audience?
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Browse Statistics Questions
Sample Answer
Problem Formulation

To calculate the expected value for user retention at Stripe, we need to define our variables clearly. Let:

  • nn = number of users in the sample
  • kk = number of users retained after a cer...
Solution Approach
  1. Data Collection: Collect data on user retention over a defined period. For instance, suppose we have a sample of 1000 users, and 250 users are retained.
  2. Calculate Retention Rate: Calcula...

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