In statistics, there are two main paradigms: classical and Bayesian statistics. The purpose of this article is to investigate the extent to which classicists and Bayesians can (in some suitable sense of the word) agree. My conclusion is that, in certain situations, they cannot. The upshot is that, if we assume that the classicist is not allowed to have a higher degree of belief (credence) in a null hypothesis after he has rejected it than before, then (in certain situations) he has to either have trivial or incoherent credences to begin with or fail to update his credences by conditionalization.

中文翻译：

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经典与贝叶斯统计

在统计学中，有两种主要范式：经典和贝叶斯统计。这篇文章的目的是调查古典主义者和贝叶斯主义者（在某些合适的意义上）可以达成一致的程度。我的结论是，在某些情况下，他们不能。结果是，如果我们假设古典主义者在拒绝原假设后不允许有比以前更高程度的信念（可信度），那么（在某些情况下）他必须要么有琐碎的要么不连贯的凭据开始或未能通过条件化更新他的凭据。