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Bayesian Statistics without Tears: A Sampling-Resampling Perspective

A. F. M. Smith and A. E. Gelfand
The American Statistician
Vol. 46, No. 2 (May, 1992), pp. 84-88
DOI: 10.2307/2684170
Stable URL: http://www.jstor.org/stable/2684170
Page Count: 5
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Bayesian Statistics without Tears: A Sampling-Resampling Perspective
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Abstract

Even to the initiated, statistical calculations based on Bayes's Theorem can be daunting because of the numerical integrations required in all but the simplest applications. Moreover, from a teaching perspective, introductions to Bayesian statistics-if they are given at all-are circumscribed by these apparent calculational difficulties. Here we offer a straightforward sampling-resampling perspective on Bayesian inference, which has both pedagogic appeal and suggests easily implemented calculation strategies.

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