Why are conditional degrees of belief in an observation E, given a statistical hypothesis H, aligned with the objective probabilities expressed by H? After showing that standard replies (ratio analysis of conditional probability, chance-credence coordination) are not satisfactory, I develop a suppositional analysis of conditional degree of belief, transferring Ramsey’s classical proposal to statistical inference. The analysis saves the alignment, explains the role of chance-credence coordination, and rebuts the charge of arbitrary assessment of evidence in Bayesian inference. Finally, I explore the implications of this analysis for Bayesian reasoning with idealized models in science.

中文翻译：

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条件置信度和贝叶斯推理

为什么在给定统计假设 H 的情况下，观察 E 的条件置信度与 H 表示的客观概率一致？在表明标准答复（条件概率的比率分析、机会-信任协调）不令人满意之后，我开发了条件置信度的假设分析，将 Ramsey 的经典建议转移到统计推断中。该分析保存了对齐，解释了机会-信任协调的作用，并反驳了贝叶斯推理中任意评估证据的指控。最后，我探索了这种分析对科学中理想化模型的贝叶斯推理的影响。