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Correlation vs Causation: Understand the Difference for Your Product

by
Archana Madhavan
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While causation and correlation can exist at the same time, correlation doesn't mean causation.

What’s the difference between correlation and causation?

  • Causation explicitly applies to cases where action A causes outcome B
  • Correlation is simply a relationship
    • Action A relates to Action B—but one event doesn’t necessarily cause the other event to happen

How to test for causation in your product

  • Run robust experiments to determine causation
    • Hypothesis testing
      • The most basic hypothesis test will involve a H0 (null hypothesis) and H1 (your primary hypothesis)
      • The null hypothesis is the opposite of your primary hypothesis
      • While you cannot prove your primary hypothesis with 100% certainty (the closest you can get is 99%), you can disprove your null hypothesis
    • When to use hypothesis testing
      • Hypothesis testing is helpful when you are trying to identify whether a relationship actually exists between two variables rather than looking at anecdotal evidence
    • A/B/n Experimentation
      • A/B/n testing can bring you from correlation to causation
      • Look at each of your variables, change one and see what happens
    • When to use A/B/n testing
      • A/B/n, or split testing, is ideal when you’re comparing the impact of different variations

Act on the right correlations for sustained product growth

  • The more adept you become at identifying true correlations within your product, the better you’ll get at prioritizing your efforts for user engagement and retention
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