解释力

J. Sprenger, S. Hartmann
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引用次数: 8

摘要

本章阐述了为什么,以及在何种情况下,一个科学假设的解释力相对于一个证据体可以通过统计相关性来解释。这种说法可以追溯到Peirce和Hempel的历史根源,并反驳了其批评者(例如,将统计相关性与纯粹的因果解释进行对比)。然后,我们用表征定理的方法推导了解释力的各种贝叶斯解释,并从规范的角度比较了它们的性质。最后,我们评估了这些解释力的度量是如何为最佳解释推理理论奠定基础的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Explanatory Power
This chapter motivates why, and under which circumstances, the explanatory power of a scientific hypothesis with respect to a body of evidence can be explicated by means of statistical relevance. This account is traced back to its historic roots in Peirce and Hempel and defended against its critics (e.g., contrasting statistical relevance to purely causal accounts of explanation). Then we derive various Bayesian explications of explanatory power using the method of representation theorems and we compare their properties from a normative point of view. Finally we evaluate how such measures of explanatory power can ground a theory of Inference to the Best Explanation (IBE).
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