Calculate variance for coin flips
Last updated: December 18, 2025
Quick Overview
Given the following scenario about revenue per session, calculate the the sample size needed.
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Given the following scenario about revenue per session, calculate the the sample size needed.
Statistics questions at LinkedIn 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
- Set up the problem formally with proper notation
- Apply the correct statistical test with clear justification
- Interpret results with appropriate caveats and confidence levels
- Discuss practical significance vs statistical significance
- Identify potential confounders and how to address them
Key Topics to Cover
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 alternative statistical method could you use here?
- How would you handle multiple comparisons?
- How would you design a follow-up experiment based on these results?
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Browse Statistics QuestionsSample Answer
Problem Formulation
We want to calculate the sample size needed to estimate the variance of revenue per session for a given treatment effect in coin flips (e.g., measuring user engagement on LinkedIn). Let's denote:
- (...
Solution Approach
- Determine Parameters: Choose a desired confidence level (e.g., 95%), which gives a Z-score of 1.96.
- Estimate Variance: Use historical data or pilot studies to estimate the variance ( \s...
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