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Title: Modeling biased information seeking with second order probability distributions (English)
Author: Kleiter, Gernot D.
Language: English
Journal: Kybernetika
ISSN: 0023-5954 (print)
ISSN: 1805-949X (online)
Volume: 51
Issue: 3
Year: 2015
Pages: 469-485
Summary lang: English
Category: math
Summary: Updating probabilities by information from only one hypothesis and thereby ignoring alternative hypotheses, is not only biased but leads to progressively imprecise conclusions. In psychology this phenomenon was studied in experiments with the “pseudodiagnosticity task”. In probability logic the phenomenon that additional premises increase the imprecision of a conclusion is known as “degradation”. The present contribution investigates degradation in the context of second order probability distributions. It uses beta distributions as marginals and copulae together with C-vines to represent dependence structures. It demonstrates that in Bayes' theorem the posterior distributions of the lower and upper probabilities approach 0 and 1 as more and more likelihoods belonging to only one hypothesis are included in the analysis. (English)
Keyword: probability logic
Keyword: Bayes' theorem
Keyword: degradation
Keyword: pseudodiagnosticity task
Keyword: second order probability distributions
MSC: 03B48
MSC: 49N30
MSC: 62F15
MSC: 62H05
MSC: 68T30
MSC: 68T35
MSC: 91E10
idZBL: Zbl 06487091
idMR: MR3391680
DOI: 10.14736/kyb-2015-3-0469
Date available: 2015-09-01T09:15:08Z
Last updated: 2016-01-03
Stable URL:
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