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Does quantum uncertainty have a place in everyday applied statistics?
Andrew Gelman1, Michael Betancourt
1Department of Statistics, Columbia University, New York, NY 10027, USA. gelman@stat.columbia.edu
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.
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