Reichenbach’s Common Cause Principle
Updated 2026-09-10
INTRODUCTION
English translation pending.
CORE DEFINITION
Hans Reichenbach's Common Cause Principle states that if two events A and B are positively correlated, with neither causing the other, then there exists a common cause C such that A and B are conditionally independent given C. The correlation must be unexplainable by any direct causal link between the events. The principle is a cornerstone of probabilistic causal inference and causal graph methods.
SCAFFOLDING EFFECT
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- Correlation attribution: when two events correlate and neither causes the other, hypothesize a common cause and test it by conditioning. - Confounder identification: use conditional independence as the criterion to uncover hidden third variables in the data.
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If two correlated events neither causes the other, the correlation must arise from structure: either an earlier common cause screens them off so that conditioning removes the correlation, or some other causal link exists. The common cause is thus the most economical explanation of the correlation, and the foundation of probabilistic causal inference and causal graphs.
MINIMUM ACTION
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Source support: Explicit
- plato.stanford.eduhttps://plato.stanford.edu/entries/physics-Rpcc/verified
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