Calculate variance for user retention
Last updated: August 27, 2025
Quick Overview
Given the following scenario about revenue per session, calculate the the sample size needed.
JPMorgan
August 27, 2025119
14
4,679 solved
Given the following scenario about revenue per session, calculate the the sample size needed.
Analytics questions at JPMorgan 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 a rigorous experiment with proper randomization and sample size calculation
- Define primary and guardrail metrics with clear rationale
- Address novelty effects, network effects, and interference
- Segment results appropriately and identify heterogeneous treatment effects
- Propose follow-up analyses when results are ambiguous
Key Topics to Cover
How to Approach This
- Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
- Run experiments long enough to account for novelty effects and weekly seasonality.
- Use funnel analysis to identify where users drop off for maximum optimization impact.
- Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
- Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
- How would you handle interference between treatment and control?
- How would you handle seasonality in your experiment?
- How would you handle an experiment where the control and treatment groups are different sizes?
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Browse Analytics QuestionsSample Answer
Problem Setup
To evaluate user retention, we need to assess the variance in revenue per session across different user segments. The specific analytical question is: "What is the sample size required to detect a mea...
Methodology
We will use a two-sample t-test for our analysis, which compares the means of two independent groups. To determine the necessary sample size, we'll apply the formula:
[ n = \frac{(Z_{\alpha/2} + Z_{...
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