Simplifying Bayesian inference : the general case

Details

Serval ID
serval:BIB_3943F7503CEA
Type
A part of a book
Collection
Publications
Title
Simplifying Bayesian inference : the general case
Title of the book
Model-based reasoning in scientific discovery
Author(s)
Krauss S., Martignon L., Hoffrage U.
Publisher
Kluwer Academic / Plenum Publishers
Address of publication
New York, NY
ISBN
978-1-4613-7181-6
978-1-4615-4813-3
Publication state
Published
Issued date
1999
Editor
Magnani L., Nersessian N. J., Thagard P.
Pages
165-179
Language
english
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 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.
Create date
24/02/2009 15:34
Last modification date
20/08/2019 14:28
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