T(h)ree steps to improve Bayesian reasoning

DOI to cite this document:: 10.5283/epub.51335

Binder, Karin

; Krauss, Stefan

; Bruckmaier, Georg ; Marienhagen, Jörg

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Date of publication of this fulltext: 15 Jun 2022 08:56

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Item type:	Conference or workshop item (Paper)
Date:	2018
Additional Information (public):	In M. A. Sorto, A. White, & L. Guyot (Eds.), Looking back, looking forward. Proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018), Kyoto, Japan. Voorburg, The Netherlands: International Statistical Institute
Institutions:	Medicine > Abteilung für Nuklearmedizin Mathematics > Prof. Dr. Stefan Krauss
Dewey Decimal Classification:	500 Science > 510 Mathematics 600 Technology > 610 Medical sciences Medicine
Status:	Unknown
Refereed:	Unknown
Created at the University of Regensburg:	Partially
Item ID:	51335

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Abstract

Physicians must frequently combine statistical information on prevalence of diseases and on medical tests according to Bayes’ theorem in order to arrive at a correct diagnosis. Such decisionmaking processes are often associated with significant errors of judgment, which have been documented repeatedly with respect to the Bayesian “standard” task (i.e., one disease must be diagnosed based on one ...

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