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9 - When are probabilistic explanations possible?

Published online by Cambridge University Press:  05 June 2012

Patrick Suppes
Affiliation:
Stanford University, California
Mario Zanotti
Affiliation:
Computer Curriculum Corporation, California
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Summary

The primary criterion of adequacy of a probabilistic causal analysis is that the causal variable should render the simultaneous phenomenological data conditionally independent. The intuition back of this idea is that the common cause of the phenomena should factor out the observed correlations. So we label the principle the common cause criterion. If we find that the barometric pressure and temperature are both dropping at the same time, we do not think of one as the cause of the other but look for a common dynamical cause within the physical theory of meteorology. If we find fever and headaches positively correlated, we look for a common disease as the source and do not consider one the cause of the other. But we do not want to suggest that satisfaction of this criterion is the end of the search for causes or probabilistic explanations. It does represent a significant and important milestone in any particular investigation.

Under another banner the search for common causes in quantum mechanics is the search for hidden variables. A hidden variable that satisfies the common cause criterion provides a satisfactory explanation “in classical terms” of the quantum phenomenon. Much of the earlier discussion of hidden variables in quantum mechanics has centered around the search for deterministic underlying processes, but for some time now the literature has also been concerned with the existence of probabilistic hidden variables. It is a striking and important fact that even probabilistic hidden variables do not always exist when certain intuitive criteria are imposed.

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Foundations of Probability with Applications
Selected Papers 1974–1995
, pp. 105 - 112
Publisher: Cambridge University Press
Print publication year: 1996

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