Calculate expected value for user retention
Last updated: February 2, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the p-value.
Pinterest
Statistics & Math
Data Scientist
Data Scientist
Technical Screen
Statistics & Math
Hard
12
6
1,076 solved
Given the following scenario about user conversion, calculate the the p-value.
Statistics questions at Pinterest test your ability to reason quantitatively and design rigorous experiments. This Technical Screen question evaluates your understanding of statistical inference and its application to business decisions.
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
Central Limit Theorem
Conditional probability and Bayes theorem
Confidence intervals and significance levels
Probability distributions
Bayesian vs frequentist inference
How to Approach This
- Define your hypotheses (H0 and H1) clearly before performing any test.
- Calculate required sample size BEFORE running an experiment, using power analysis.
- Remember the Central Limit Theorem: sample means become approximately normal with large n.
- Watch for Simpson's paradox. Always segment data by key dimensions.
- Distinguish between statistical significance and practical significance.
Possible Follow-up Questions
- What if the sample size is very small?
- How would you explain this result to a non-technical audience?
- What alternative statistical method could you use here?
- What assumptions does this test make, and how would you validate them?
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Browse Statistics QuestionsSample Answer
Problem formulation
To calculate the expected value for user retention at Pinterest, we first need to establish a framework. Let’s assume we have data on user conversion rates from a recent campaign. We define:
- Let ( ...
Solution approach
- Data Collection: Gather data on user retention before and after the campaign. For this example, assume:
- Before the campaign: (retention rate = ...
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