Calculate variance for A/B test results
Last updated: August 30, 2025
Quick Overview
Given the following scenario about revenue per session, calculate the the p-value.
Capital One
August 30, 202519
4
4,169 solved
Given the following scenario about revenue per session, calculate the the p-value.
Capital One asks this during the Phone Screen 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 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
- What if you discover a bug in the logging during the experiment?
- How would you handle interference between treatment and control?
- How would you handle seasonality in your experiment?
- What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
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Browse Analytics QuestionsSample Answer
Problem Setup
To analyze the A/B test results for revenue per session at Capital One, we need to frame our analytical question: 'Is there a statistically significant difference in revenue per session between the co...
Methodology
In this scenario, we will utilize a two-sample t-test to calculate the p-value for the difference in means between the control group and the treatment group. This statistical approach is appropriate a...
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