Abstract
A mathematical science ordinarily admits of two (or more) possible routes to a solution. This is also true in statistics, with one notable exception. There are two fundamentally different approaches to solving certain statistical problems. These are the Bayesian and Classical1 approaches. Both camps have strong and vocal partisans, and both approaches give correct answers within their frameworks. As is usual in great controversies, the argument arises out of a difference in point of view.
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References
J. Weber: Historical Aspects of the Bayesian Controversy (University of Arizona, Tucson 1973)
A Papoulis: Probability, Random Variables and Stochastic Processes (McGraw-Hill, New York 1965)
E. Parzen: Modern Probability Theory and Its Applications (Wiley, New York 1960)
B. R. Frieden: Found. Phys. 16, 883 (1986)
Additional Reading
Good, I. J.: “The Bayesian Influence, or How to Sweep Subjectivism Under the Carpet,” in Foundations of Probability Theory, Statistical Inference, and Statistical Theories of Science, Vol. II, ed. by W. L. Harper, C. A. Hooker (Reidel, Boston 1976)
Jaynes, E. T.: “Confidence Intervals vs Bayesian Intervals”, in preceding reference
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© 1991 Springer-Verlag Berlin Heidelberg
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Frieden, B.R. (1991). The Controversy between Bayesians and Classicists. In: Probability, Statistical Optics, and Data Testing. Springer Series in Information Sciences, vol 10. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-97289-8_16
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DOI: https://doi.org/10.1007/978-3-642-97289-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53310-8
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