Significance Tests, Belief Calculi, and Burden of Proof in Legal and Scientific Discourse

Frontiers in Artificial Intelligence and Applications 101:139-147 (2003)
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Abstract

We review the definition of the Full Bayesian Significance Test (FBST), and summarize its main statistical and epistemological characteristics. We review also the Abstract Belief Calculus (ABC) of Darwiche and Ginsberg, and use it to analyze the FBST’s value of evidence. This analysis helps us understand the FBST properties and interpretation. The definition of value of evidence against a sharp hypothesis, in the FBST setup, was motivated by applications of Bayesian statistical reasoning to legal matters where the sharp hypotheses were defendants statements, to be judged according to the Onus Probandi juridical principle.

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Julio Michael Stern
University of São Paulo

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