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When can statistical theories be causally closed?

Gyenis, Balazs and Redei, Miklos (2002) When can statistical theories be causally closed? [Preprint]

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Abstract

The notion of common cause closedness of a classical, Kolmogorovian probability space with respect to a causal independence relation between the random events is defined, and propositions are presented that characterize common cause closedness for specific probability spaces. It is proved in particular that no probability space with a finite number of random events can contain common causes of all the correlations it predicts; however, it is demonstrated that probability spaces even with a finite number of random events can be common cause closed with respect to a causal independence relation that is stronger than logical independence. Furthermore it is shown that infinite, atomless probability spaces are always common cause closed in the strongest possible sense. Open problems concerning common cause closedness are formulated and the results are interpreted from the perspective of Reichenbach's Common Cause Principle.


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Item Type: Preprint
Creators:
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Gyenis, Balazs
Redei, Miklos
Keywords: probabilistic causation, Reichenbach's common cause principle
Subjects: General Issues > Causation
Depositing User: Miklos Redei
Date Deposited: 16 Jul 2002
Last Modified: 07 Oct 2010 15:10
Item ID: 675
URI: http://philsci-archive.pitt.edu/id/eprint/675

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