Explain instrumental variables with an example

Last updated: March 20, 2026

Quick Overview

Explain instrumental variables in simple terms and provide a concrete example.

Microsoft
Analytics & Experimentation
Product Manager
Microsoft
March 20, 2026
Product Manager
Onsite
Analytics & Experimentation
Hard

45

3

2,487 solved


Explain instrumental variables in simple terms and provide a concrete example.

This analytics question from Microsoft's Onsite 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
  • 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
Segmentation and heterogeneous effects
Novelty and primacy effects
Sample size and power calculation
Simpson's paradox and ecological fallacy
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 if you discover a bug in the logging during the experiment?
  • How would you handle seasonality in your experiment?
  • How would you handle interference between treatment and control?
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