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On the prior probability in the theory of sampling

Published online by Cambridge University Press:  24 October 2008

Harold Jeffreys
Harold Jeffreys
Affiliation:
St John's College
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Extract

1. If a class consists of n members of which r have the property φ, and we wish to estimate r by the process of sampling, the distribution of probability among values of r, given the composition of the sample, necessarily depends to some extent on our previous knowledge. This is expressed by saying that the prior probability of a particular value of r is f(r). According to Laplace's theory f(r) is constant. It is obvious that there are cases where the previous knowledge is such as to ensure that f(r) is not constant; but the question remains whether such cases should be considered the exception or the rule.

Type
Research Article
Information
Mathematical Proceedings of the Cambridge Philosophical Society , Volume 29 , Issue 1 , January 1933 , pp. 83 - 87
Copyright
Copyright © Cambridge Philosophical Society 1933

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References

* Jeffreys, , Scientific Inference, 1931, 29–31.Google Scholar

* Proc. Camb. Phil. Soc. 28 (1932), 58.Google Scholar

* Loc. cit. 195.

† The terms prior and a priori are not synonymous. A priori knowledge is what we should believe independently of experience, and covers the laws of logic, mathematics, and probability. Prior knowledge covers all the knowledge that we may have before the carrying out of the actual experiment under consideration, and therefore includes a great deal of previous experience that may be relevant to the prior probability.

* Proc. Camb. Phil. Soc. 28 (1932), 257–261.Google Scholar

* Wrinch, and Jeffreys, , Phil. Mag. 38 (1919), 715–731CrossRefGoogle Scholar; Jeffreys, , Scientific Inference, 33.Google Scholar