Calculate conditional probability for A/B test results

Last updated: March 30, 2026

Quick Overview

Given the following scenario about revenue per session, calculate the the p-value.

Confluent
Analytics & Experimentation
Data Scientist
Confluent
March 30, 2026
Data Scientist
Technical Screen
Analytics & Experimentation
Easy

10

0

2,269 solved


Given the following scenario about revenue per session, calculate the the p-value.

This analytics question from Confluent's Technical Screen tests your ability to think critically about data. The interviewer expects you to consider confounding variables, selection bias, and the difference between correlation and causation.

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
Funnel analysis and cohort analysis
Metric definition and success criteria
Long-term vs short-term metrics
Sample size and power calculation
Guardrail metrics
Network effects and interference
How to Approach This
  1. Define success metrics carefully. A good metric is measurable, actionable, and aligned with business goals.
  2. Run experiments long enough to account for novelty effects and weekly seasonality.
  3. Use funnel analysis to identify where users drop off for maximum optimization impact.
  4. Segment results by key dimensions (platform, country, user cohort) to catch hidden patterns.
  5. Consider network effects and interference between treatment and control groups.
Possible Follow-up Questions
  • 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?
  • What if you discover a bug in the logging during the experiment?
  • How would you handle seasonality in your experiment?
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