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

Simplifying Bayesian Inference: The General Case

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

Date of publication of this fulltext: 02 Sep 2016 08:29
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Abstract

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

Item typeBook section
ISBN0-306-46292-3
Title of Book:Model-based reasoning in scientific discovery
Publisher:Kluwer Academic/Plenum
Place of Publication:New York
Page Range:pp. 165-179
Date1999
InstitutionsMathematics > Prof. Dr. Stefan Krauss
Identification Number
ValueType
10.1007/978-1-4615-4813-3_11DOI
Dewey Decimal Classification500 Science > 510 Mathematics
StatusPublished
RefereedUnknown
Created at the University of RegensburgUnknown
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-344878
Item ID34487

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