Bayes Theorem and the cMPE-Method: Differences, Complementarities and the Importance of Discerning between Weight-bearing and Extensional Evidence

Mathematics – Statistics Theory

Scientific paper

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16 pages 7 figures

Scientific paper

Both, Bayes Theorem and the cMPE-Method serve for establishing relations between systems of probabilities. By the cMPE-Method non-conditional probabilities are added, by the DPE-Method, they are subtracted, however, in both versions allowing for the non-linearity of non-disjunctive probabilities. Semantic independence is prerequisite. As compared with the results of semantically homogeneous series of observations, the variety of evidence permits arrival at higher probabilities. The advantage of the Bayesian method lies in allowing for evidence extraneous to the domain covered by the hypothesis. We must differentiate between extensional and weight-bearing evidence. Operations based on purely weight-bearing evidence (cMPE-Method) neglect the extensional evidence and some operations according to Bayes Theorem may neglect weight-bearing evidence at least partially. These and some other shortcomings may be remedied by operations, combining both of the approaches.

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