Calculate conditional probability for user retention

Last updated: September 3, 2025

Quick Overview

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

MongoDB
Analytics & Experimentation
Data Scientist
MongoDB
September 3, 2025
Data Scientist
Phone Screen
Analytics & Experimentation
Hard

6

9

646 solved


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

MongoDB 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 complex experimentation strategies for tricky scenarios
  • Handle multi-armed bandits, switchback experiments, and quasi-experiments
  • Address long-term effects vs short-term metrics
  • Propose causal inference methods when randomization is not possible
  • Build a measurement framework that connects metrics to business value
  • Discuss organizational experimentation culture and maturity
Key Topics to Cover
Long-term vs short-term metrics
Guardrail metrics
Funnel analysis and cohort analysis
Sample size and power calculation
Metric definition and success criteria
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 seasonality in your experiment?
  • What if the experiment shows a positive short-term effect but you suspect a negative long-term impact?
  • How would you handle interference between treatment and control?
  • What would you do if a stakeholder wants to end the experiment early because initial results look good?
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