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Bayesian Statistics in Radiocarbon Calibration

Published online by Cambridge University Press:  01 April 2022

Daniel Steel
Daniel Steel*
Affiliation:
University of Pittsburgh
*
†Send requests for reprints to the author, 1017 Cathedral of Learning, University of Pittsburgh, Pittsburgh, PA 15260; email: dpsst19+@pitt.edu.
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Abstract

Critics of Bayesianism often assert that scientists are not Bayesians. The widespread use of Bayesian statistics in the field of radiocarbon calibration is discussed in relation to this charge. This case study illustrates the willingness of scientists to use Bayesian statistics when the approach offers some advantage, while continuing to use orthodox methods in other contexts. The case of radiocarbon calibration, therefore, suggests a picture of statistical practice in science as eclectic and pragmatic rather than rigidly adhering to any one theoretical position.

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Footnotes

‡

I would like to thank Clark Glymour, Deborah Mayo, John Norton, and John Earman for helpful comments on earlier drafts of this essay.

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