Do-Calculus
Updated 2026-08-09
INTRODUCTION
English translation pending.
CORE DEFINITION
Do-Calculus is a mathematical framework for causal inference developed by Judea Pearl. Its central concept is do(X=x), which represents an intervention on variable X rather than an observation of it, and it distinguishes observation from intervention because P(Y given X=x) is not equal to P(Y given do(X=x)). Its three rules allow inserting and deleting observations under certain conditions, swapping actions for observations under certain conditions, and inserting or deleting the do operator under certain conditions. The framework gives researchers a rigorous tool for inferring causal effects from observational data, which addresses the root problem that correlation is not causation.
SCAFFOLDING EFFECT
Reduce cognitive load
- Ask the interventional question: phrase the target as P(Y given do(X)), not a mere conditional. - Test identifiability: apply the three rules to see whether the data can answer it. - Never equate the two: remember that observing X fundamentally differs from setting X.
Anchor fast decisions
A mathematical causal inference framework developed by Judea Pearl. It separates observation from intervention, where P(Y given X=x) is not P(Y given do(X=x)), and the do operator denotes active intervention; the three rules then determine whether a causal quantity is identifiable from observational data, making the claim that correlation is not causation formal and computable.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
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Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Do-calculusverified
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