By Herbert A. Simon
We admire Herbert A. Simon as a longtime chief of empirical and logical research within the human sciences whereas we fortunately ponder him as additionally the loner; in fact he works with many colleagues yet none can fit him. He has been writing fruitfully and progressively for 4 a long time in lots of fields, between them psychology, common sense, selection thought, economics, laptop technology, administration, creation engineering, info and regulate conception, operations study, affirmation conception, and we should have passed over a number of. With them all, he's right away the technical scientist and the philosophical critic and analyst. while writing of selections and activities, he's on the interface of philosophy of technology, selection thought, philosophy of the categorical social sciences, and stock concept (itself, for him, on the interface of monetary thought, creation engineering and data theory). whilst writing on causality, he's on the interface of technique, metaphysics, good judgment and philosophy of physics, platforms idea, etc. now not that the interdisciplinary is his orthodoxy; we're thrilled that he has selected to incorporate during this booklet either his early and little-appreciated therapy of easy philosophy of physics - the axioms of Newtonian mechanics, and likewise his nice papers on natural affirmation theory.
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If the generalization fits the facts, the resulting array of points will (1) fall on a straight line, (2) with a slope of minus one. Since we earlier rejected the standard statistical tests of hypotheses as inappropriate to this situation, we are left with only judgmental processes for deciding whether the data fall on a straight line. It is not true, as is sometimes suggested, that almost any ranked data will fallon a straight line when graphed on doubly logarithmic paper. It is quite easy to find data that are quite curvilinear to the naked eye (see Figure 3).
Neyman, 'Basic Ideas and Some Results of the Theory of Testing Statistical Hypotheses', Journal of the Royal Statistical Society 105,304 (1942). ST A TlSTICA L TE STS 19 It should perhaps be pointed out that the difference in cost between the two treatments should include all costs, not excepting interest and depreciation on investment to be made. This raises the troublesome question whether, in setting the depreciation rates, the risk should be included that after the investment has been made the treatment now thought preferable may be found the less desirable of the two on the basis of additional data, and may therefore be discontinued.
Such a definition of degree of confirmation apparently violates some of our intuitive beliefs about the dependence of the efficacy of evidence upon the time when it is discovered. Let us suppose that the hypothesis h implies the two observational propositions e 1 and e2. Scientist A makes the observation e 1 , formulates the hypothesis h to explain his observation, predicts e2 in the basis of h, and subsequently observes e2. Scientist B makes the observations el and e2, and formulates the hypothesis h to explain them.