Explain regression discontinuity with an example

Last updated: January 7, 2026

Quick Overview

Explain regression discontinuity in simple terms and provide a concrete example.

Jane Street
Analytics & Experimentation
Data Scientist
Jane Street
January 7, 2026
Data Scientist
Technical Screen
Analytics & Experimentation
Medium

5

12

1,218 solved


Explain regression discontinuity in simple terms and provide a concrete example.

This analytics question from Jane Street'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
  • 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
Sample size and power calculation
Segmentation and heterogeneous effects
Long-term vs short-term metrics
Funnel analysis and cohort analysis
Novelty and primacy effects
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?
  • 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?
  • How would you handle seasonality in your experiment?
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