Calculate conditional probability for coin flips

Last updated: August 26, 2025

Quick Overview

Given the following scenario about revenue per session, calculate the the sample size needed.

Microsoft
Analytics & Experimentation
Data Scientist
Microsoft
August 26, 2025
Data Scientist
Take-home Project
Analytics & Experimentation
Easy

5

5

1,250 solved


Given the following scenario about revenue per session, calculate the the sample size needed.

This analytics question from Microsoft's Take-home Project 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
A/B testing methodology
Segmentation and heterogeneous effects
Network effects and interference
Funnel analysis and cohort analysis
Long-term vs short-term metrics
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
  • What would you do if a stakeholder wants to end the experiment early because initial results look good?
  • How would you handle an experiment where the control and treatment groups are different sizes?
  • 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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