Inverse Probability and Modern Statisticians

Abstract

Introduction: Purpose of this essay is to draw attention to some points which are relevant to the underlying philosophy of modern statistics, but which the writer feels have been largely overlooked both by the defenders and the opponents of the classic conceptions of Laplace. There is no quarrel with methodologies as such which have found their introduction under the heads of “maximum likelihood”, “fiducial limits”, etc. But the writer cannot accept arguments (e.g. Fisher (1)) which would make of such procedures an absolute sine qua non for all decisions based on evidence, and which would relegate human judgment (a priori probabilities) and all considerations of the intended use of a decision to the rubbish heap of outmoded conceptions. To assume that two rational minds, having different backgrounds and different objectives, must necessarily find themselves in agreement in their appraisal of a given objective situation, is simply absurd; yet this is the basis which underlies, so far as I can make out, all the “criticisms” of Laplace and Bayes which constitute the excuses put forward for attempting to displace those procedures in Statistics which involve “inverse probability”. Also the so-called “paradoxes” which have been invented by many writers in order to assail Laplace, contradict only this one assumption; without it they are not paradoxes.