Machine Learning
Causal Inference
Statistical methods for determining cause-and-effect relationships from data, going beyond correlation to understand whether X actually causes Y.
Why It Matters
Causal inference prevents costly mistakes — 'Users who buy premium also use feature X' does not mean forcing feature X will drive premium sales.
Example
Determining whether a new onboarding flow actually caused increased retention, or whether the improvement was just due to seasonal effects or a concurrent marketing campaign.
Think of it like...
Like a doctor determining whether a medication cured the patient versus the patient recovering naturally — correlation (took medicine and got better) does not prove causation.