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Does quantum uncertainty have a place in everyday applied statistics?

Published online by Cambridge University Press:  14 May 2013

Andrew Gelman  and
Michael Betancourt
Andrew Gelman
Affiliation:
Department of Statistics, Columbia University, New York, NY 10027. gelman@stat.columbia.edubetanalpha@gmail.comhttp://www.stat.columbia.edu/~gelman
Michael Betancourt
Affiliation:
Department of Statistics, Columbia University, New York, NY 10027. gelman@stat.columbia.edubetanalpha@gmail.comhttp://www.stat.columbia.edu/~gelman
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Abstract

We are sympathetic to the general ideas presented in the article by Pothos & Busemeyer (P&B): Heisenberg's uncertainty principle seems naturally relevant in the social and behavioral sciences, in which measurements can affect the people being studied. We propose that the best approach for developing quantum probability models in the social and behavioral sciences is not by directly using the complex probability-amplitude formulation proposed in the article, but rather, more generally, to consider marginal probabilities that need not be averages over conditionals.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 36 , Issue 3 , June 2013 , pp. 285
Copyright
Copyright © Cambridge University Press 2013 

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