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The Probability Concept

Published online by Cambridge University Press:  14 March 2022

Edwin C. Kemble*
Affiliation:
Harvard University

Extract

The writer of this paper is not an expert on probability from either the mathematical or the philosophical side, but a theoretical physicist forced by the exigencies of work in his own field to make his peace with the concept of probability. The present contribution is a sequel to remarks on two different types of probability in a recent paper on the relation between statistical mechanics and thermodynamics.

Type
Research Article
Copyright
Copyright © The Philosophy of Science Association 1941

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References

1 Kemble, E. C., Phys. Rev. 56, 1013-23 (1939). Cf. especially pp. 1018-19.Google Scholar

2 Cf., e.g., Bridgman, P. W., Phil. Sci. 5, 114 (1938).CrossRefGoogle Scholar

3 Cf. Kemble, E. C., Fundamental Principles of Quantum Mechanics, New York, 1937, pp. 53-55.Google Scholar

4 The term “likelihood” is used in its nontechnical sense.Google Scholar

5 Jeffreys, H., Theory of Probability, Oxford, 1939, p. 8.Google Scholar

6 In defining probabilities as numbers we go a short distance with the advocates of the frequency definition!Google Scholar

7 Keynes has amply set forth the related absurdity of supposing that a definite numerical probability can be assigned to the logical relation between any set of premises and any possible conclusion. Cf. his Treatise on Probability, London, 1921, Chapter III.Google Scholar

8 Cf. Born, Max, Proc. Roy. Soc. Edinburgh, 57, 1, (1936).CrossRefGoogle Scholar

9 Cf. Mach, E., Principien der Wärmelehre, 4th (posthumous) ed., Leipsic, 1922, p. 46. The doctrine that science is an analysis of experience is central in the positivistic philosophy of Mach. This is to my mind the quintessence of operationalism. I hold no brief here for positivism as a complete philosophy, but because I believe that natural science must avoid hidden assumptions and obscurantism as it would the pestilence, I am convinced that this kind of activity should be carried out on a positivistic basis.Google Scholar

10 Beliefs do not always relate to the future and are to a large extent staged in the external world of common sense. Nevertheless they can be reduced in large part to operational terms and are then equivalent to expectancies regarding what would happen if certain experiments were performed. I shall not concern myself with probabilities originating in beliefs not reducible to operational terms.Google Scholar

11 The view of Keynes that probability should be defined as an objective logical relation between propositions is closely related to my conclusion that probability is best regarded as a number relating given data with a suggested event and computed by rules designed to secure that reliability which we associate with the adjective “objective”. The difference is primarily one of philosophic bias and reflects in part my skepticism of the traditional view of logic and mathematics as repositories of external objective “truth”.Google Scholar

12 As an example consider the case of a gas at a very low pressure through which an electrical discharge is passing. In such a case the free electrons can have one effective temperature, the translational motion of the molecules a second, and the rotational motion of the molecules a third. For the system as a whole there is no definite temperature.Google Scholar

13 This fact was first impressed upon me by my colleague, Prof. Bridgman. 14 Cf. D. L. Miller, Philosophy of Science, 7, 26 (1940).Google Scholar

15 Here I use the word “implies” as quivalent to “creates a practical certainty that the event in question will occur”. It does not signify a logical connection.Google Scholar

16 Cf. Introduction to Mathematical Probability, J. V. Uspensky, New York, 1937, Chapter 2.Google Scholar

17 Peirce, C. S., Theory of Probable Inference, pp. 172-3.Google Scholar

18 Keynes, J. M., A Treatise on Probability, 1921, pp. 56-7.Google Scholar

19 Jeffreys, H., l.c., p. 100.Google Scholar

20 See, for example, Tolman, R. C., The Principles of Statistical Mechanics, Oxford, 1938, pp. 59-63.Google Scholar

21 Cf. von Neumann, J.Zeits. f. Physik 57 30-70 (1929); Kemble, E. C., Phys. Rev. 56, 1146-64 (1939).Google Scholar

22 I take the nomenclature from Jeffreys, l.c., p. 41.Google Scholar

23 I mean tests to locate the center of gravity and fix the ellipsoid of inertia.Google Scholar

24 At this point we touch on the great problem of statistical control. Cf. e.g., W. A. Shewhart, Statistical Method from the Viewpoint of Quality Control, Washington, 1939.Google Scholar

25 Broad, C. D., Mind, 27, 389 404 (1918); Jeffreys, l.c., p. 105. Jeffreys also gives a formula for the probability that w‘ of the next n‘ draws will be white, a result again independent of N.CrossRefGoogle Scholar

26 Jeffreys, H., l.c., p. 113. The notation of Eq. (3) comes from Jeffreys.Google Scholar