Why isn't everyone a bayesian?

@inproceedings{Efron1986WhyIE,
  title={Why isn't everyone a bayesian?},
  author={Bradley Efron},
  year={1986}
}
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… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-6 OF 6 REFERENCES

The Coverage Probability of Confidence Sets

C. Stein
  • 1982

" The Future of Statistics - A Bayesian 21 st Century , " Supp

D. V. Lindley
  • Adv . Appl . Prob . , 7 , 106 - 115 . - - ( 1982 ) , " Scoring Rules and the Inevitability of Probability , " ISi Review
  • 1975