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Krauss, Stefan ; Martignon, L. ; Hoffrage, U.

Simplifying Bayesian Inference: The General Case

Krauss, Stefan , Martignon, L. und Hoffrage, U. (1999) Simplifying Bayesian Inference: The General Case. In: Magnani, Lorenzo und Nersessian, Nancy J. und Thagard, Paul, (eds.) Model-based reasoning in scientific discovery. Kluwer Academic/Plenum, New York, S. 165-179. ISBN 0-306-46292-3.

Veröffentlichungsdatum dieses Volltextes: 02 Sep 2016 08:29
Buchkapitel


Zusammenfassung

We present empirical evidence that human reasoning follows the rules of probability theory, if information is presented in “natural formats”. Human reasoning has often been evaluated in terms of humans’ ability to deal with probabilities. Yet, in nature we do not observe probabilities, we rather count samples and their subsets. Our concept of Markov frequencies generalizes Gigerenzer and ...

We present empirical evidence that human reasoning follows the rules of probability theory, if information is presented in “natural formats”. Human reasoning has often been evaluated in terms of humans’ ability to deal with probabilities. Yet, in nature we do not observe probabilities, we rather count samples and their subsets. Our concept of Markov frequencies generalizes Gigerenzer and Hoffrage’s “natural frequencies”, which are known to foster insight in Bayesian situations with one cue. Markov frequencies allow to visualize Bayesian inference problems even with an arbitrary number of cues.



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Details

DokumentenartBuchkapitel
ISBN0-306-46292-3
Buchtitel:Model-based reasoning in scientific discovery
Verlag:Kluwer Academic/Plenum
Ort der Veröffentlichung:New York
Seitenbereich:S. 165-179
Datum1999
InstitutionenMathematik > Prof. Dr. Stefan Krauss
Identifikationsnummer
WertTyp
10.1007/978-1-4615-4813-3_11DOI
Dewey-Dezimal-Klassifikation500 Naturwissenschaften und Mathematik > 510 Mathematik
StatusVeröffentlicht
BegutachtetUnbekannt / Keine Angabe
An der Universität Regensburg entstandenUnbekannt / Keine Angabe
URN der UB Regensburgurn:nbn:de:bvb:355-epub-344878
Dokumenten-ID34487

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