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Why Isn't Everyone a Bayesian?

B. Efron
The American Statistician
Vol. 40, No. 1 (Feb., 1986), pp. 1-5
DOI: 10.2307/2683105
Stable URL: http://www.jstor.org/stable/2683105
Page Count: 5
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Why Isn't Everyone a Bayesian?
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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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