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Cited by 377

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Why Isn't Everyone a Bayesian?

Efron, B.·1986·The American Statistician

Abstract

Originally a talk delivered at a conference on Bayesian statistics, this article attempts to answer the following question: why is most scientific data analysis carried out in a non-Bayesian framework? The argument consists mainly of some practical examples of data analysis, in which the Bayesian approach is difficult but Fisherian/frequentist solutions are relatively easy. There is a brief discussion of objectivity in statistical analyses and of the difficulties of achieving objectivity within a Bayesian framework. The article ends with a list of practical advantages of Fisherian/frequentist methods, which so far seem to have outweighed the philosophical superiority of Bayesianism.

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Metadata

Authors
Efron, B.
Venue
The American Statistician
Published
1986-02
Volume
40
Issue
1
Pages
1-5
ISSN
  • 0003-1305 (ISSN-L)
  • 1537-2731
OpenAlex
W2017529320
Cited by
377
References
10
FWCI
12.65
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Why Isn't Everyone a Bayesian? https://app.cochat.ai/papers/10.1080/00031305.1986.10475342
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Efron, B. (1986). Why Isn't Everyone a Bayesian? The American Statistician. https://doi.org/10.1080/00031305.1986.10475342

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