Calculate probability for click-through rates
Last updated: February 28, 2026
Quick Overview
Given the following scenario about user conversion, calculate the the p-value.
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Given the following scenario about user conversion, calculate the the p-value.
Analytics questions at LinkedIn 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
- Define clear success metrics aligned with business goals
- Propose a basic experimental design with control and treatment groups
- Interpret results correctly and draw reasonable conclusions
- Identify obvious confounding variables
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 seasonality in your experiment?
- How would you handle interference between treatment and control?
- What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
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