Skip to main content

Part of the book series: Fundamental Theories of Physics ((FTPH,volume 39))

Abstract

At the 1988 workshop we called attention to the “Mind Projection Fallacy” which is present in all fields that use probability. Here we give a more complete discussion showing why probabilities need not correspond to physical causal influences, or “propensities” affecting mass phenomena. Probability theory is far more useful if we recognize that probabilities express fundamentally logical inferences pertaining to individual cases. We note several examples of the difference this makes in real applications.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • P. Armitage (1975), Sequential Medical Trials, Thomas, Springfield, Illinois. Second edition: Blackwell, Oxford.

    Google Scholar 

  • G. Larry Bretthorst (1988), Bayesian Spectrum Analysis and Parameter Estimation, Springer Lecture Notes in Statistics, Vol. 48.

    MATH  Google Scholar 

  • Peter Cheeseman (1988), “An inquiry into computer understanding”, Comput. In tell. 4, 58–66. See also the following 76 pages of discussion.

    Article  Google Scholar 

  • H.E. Kyburg (1987), “The Basic Bayesian Blunder”, in Foundations of Statistical Inference, Vol II, I. B. MacNeill & G. J. Umphrey, Editors, Reidel Publishing Company, Holland.

    Google Scholar 

  • Mark Kac (1956), it Some Stochastic Problems in Physics and Mathematics; Colloquium Lectures in Pure and Applied Science #2, Socony-Mobil Oil Company, Dallas, Texas.

    Google Scholar 

  • R. Pool (1989), “Chaos Theory: How Big an Advance?”, Science, 245, 26–28.

    Article  Google Scholar 

  • L. J. Savage (1962) The Foundations of Statistical Inference, G. A. Barnard & D. R. Cox, Editors, Methuen k Co., Ltd., London

    Google Scholar 

  • Dan Shafer (1989), “Ask the Expert”, PC AI Magazine, May/June; p. 70.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1990 Kluwer Academic Publishers

About this chapter

Cite this chapter

Jaynes, E.T. (1990). Probability Theory as Logic. In: Fougère, P.F. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 39. Springer, Dordrecht. https://doi.org/10.1007/978-94-009-0683-9_1

Download citation

  • DOI: https://doi.org/10.1007/978-94-009-0683-9_1

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-010-6792-8

  • Online ISBN: 978-94-009-0683-9

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics