Calculate conditional probability for A/B test results

Last updated: September 1, 2025

Quick Overview

Given the following scenario about user conversion, calculate the the sample size needed.

Adobe
Analytics & Experimentation
Data Scientist
Adobe
September 1, 2025
Data Scientist
Phone Screen
Analytics & Experimentation
Medium

22

2

2,886 solved


Given the following scenario about user conversion, calculate the the sample size needed.

Analytics questions at Adobe evaluate your ability to define metrics, design experiments, and derive actionable insights from data. This Phone Screen 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
Novelty and primacy effects
Long-term vs short-term metrics
Metric definition and success criteria
A/B testing methodology
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 would you do if a stakeholder wants to end the experiment early because initial results look good?
  • What if you discover a bug in the logging during the experiment?
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