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Unformatted text preview: Enumerative vs Analytic Studies The Scientific Method There are three key steps in the scientific method: The origin of a theory or working hypothesis Experimentation and testing of the theory or working hypothesis Confirmation and the development of confidence in predictions based on the theory or working hypothesis through the nontrivial replication of results. The Scientific Method, Statistical Theory, and Applications The power of the scientific method rests on its integration of content knowledge and experience with prediction, experimentation, and confirmation. In any realm where these elements form the basis for rational decision making, and the nontrivial replication of results forms the basis for confirmation, the principles of the scientific method are at work. The Scientific Method, Statistical Theory, and Applications In 1921 Albert Einstein noted, As far as the laws of mathematics refer to reality, they are not certain; and as far as they are certain, they do not refer to reality. In 1931 Walter Shewhart noted, The fact that the criterion which we happen to use has a fine ancestry of mathematical statistical theorems does not justify its use. Such justification must come from empirical evidence that it works. The Scientific Method, Statistical Theory, and Applications In 1965 J. T. Davies noted, The same uncertainty, stemming from possible ignorance of some additional factor, makes the application of mathematical probability theory logically indefensible in scientific predictions. Indeed, mathematical probability, like other mathematical deductions, is part of a strictly logical system, and is always true in the sense that, given the premises (assumptions) and the deductive rules to be used, the result has been obtained correctly. Truth is thus a word we may use of a mathematical or logical deduction, but it is not one we should ever use of a scientific theory. The latter can best be described as a welltested and precise working hypothesis. A Provocative Quote from Dr. Deming The teaching of pure statistical theory in universities, including the theory of probability and related subjects is almost everywhere excellent. Application to enumerative studies is mostly correct, but application to analytic problems planning for improvement of tomorrows run, next years crop is unfortunately, however, in many textbooks deceptive and misleading. Analysis of variance, ttests, confidence intervals, and other statistical techniques taught in books, however interesting, are inappropriate because they provide no basis for prediction and because they bury the information contained in the order of production. The student should avoid passages in books that treat confidence intervals and tests of significance, as such calculations have no application in analytic problems of science and industry. W. Edwards Deming, Out of the Crisis, 1986 Enumerative Versus Analytic Studies...
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 Fall '11
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