Book contents
- Frontmatter
- Contents
- Editor's foreword
- Preface
- Part I Principles and elementary applications
- Part II Advanced applications
- 11 Discrete prior probabilities: the entropy principle
- 12 Ignorance priors and transformation groups
- 13 Decision theory, historical background
- 14 Simple applications of decision theory
- 15 Paradoxes of probability theory
- 16 Orthodox methods: historical background
- 17 Principles and pathology of orthodox statistics
- 18 The Ap distribution and rule of succession
- 19 Physical measurements
- 20 Model comparison
- 21 Outliers and robustness
- 22 Introduction to communication theory
- Appendix A Other approaches to probability theory
- Appendix B Mathematical formalities and style
- Appendix C Convolutions and cumulants
- References
- Bibliography
- Author index
- Subject index
17 - Principles and pathology of orthodox statistics
from Part II - Advanced applications
Published online by Cambridge University Press: 05 September 2012
- Frontmatter
- Contents
- Editor's foreword
- Preface
- Part I Principles and elementary applications
- Part II Advanced applications
- 11 Discrete prior probabilities: the entropy principle
- 12 Ignorance priors and transformation groups
- 13 Decision theory, historical background
- 14 Simple applications of decision theory
- 15 Paradoxes of probability theory
- 16 Orthodox methods: historical background
- 17 Principles and pathology of orthodox statistics
- 18 The Ap distribution and rule of succession
- 19 Physical measurements
- 20 Model comparison
- 21 Outliers and robustness
- 22 Introduction to communication theory
- Appendix A Other approaches to probability theory
- Appendix B Mathematical formalities and style
- Appendix C Convolutions and cumulants
- References
- Bibliography
- Author index
- Subject index
Summary
The development of our theory beyond this point, as a practical statistical theory, involves … all the complexities of the use, either of Bayes' law on the one hand, or of those terminological tricks in the theory of likelihood on the other, which seem to avoid the necessity for the use of Bayes' law, but which in reality transfer the responsibility for its use to the working statistician, or the person who ultimately employs his results.
Norbert Wiener (1948)To the best of our knowledge, Norbert Wiener never actually applied Bayes' theorem in a published work; yet he perceived the logical necessity of its use as soon as one builds beyond the sampling distributions involved in his own statistical work. In the present chapter we examine some of the consequences of failing to use Bayesian methods in some very simple problems, where the paradoxes of Chapter 15 never arise.
In Chapter 16 we noted that the orthodox objections to Bayesian methods were always philosophical or ideological in nature, never examining the actual results that they give, and we expressed astonishment that mathematically competent persons would use such arguments. In order to give a fair comparison, we need to adopt the opposite tactic here, and concentrate on the demonstrable facts that orthodoxians never mention. Since Bayesian methods have been so egregiously misrepresented in the orthodox literature throughout our lifetimes, we must lean over backwards to avoid misrepresenting orthodox methods now; whenever an orthodox method does yield a satisfactory result in some problem, we shall acknowledge that fact, and we shall not deplore its use merely on ideological grounds.
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- Chapter
- Information
- Probability TheoryThe Logic of Science, pp. 509 - 552Publisher: Cambridge University PressPrint publication year: 2003