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Using the Coefficient of Confidence to Make the Philosophical Switch From A Posteriori to A Priori Inferential Statistics

机译:利用置信系数使哲学开关从后验中发出哲学开关到先验的推理统计数据

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>There has been much controversy over the null hypothesis significance testing procedure, with much of the criticism centered on the problem of inverse inference. Specifically, p gives the probability of the finding (or one more extreme) given the null hypothesis, whereas the null hypothesis significance testing procedure involves drawing a conclusion about the null hypothesis given the finding. Many critics have called for null hypothesis significance tests to be replaced with confidence intervals. However, confidence intervals also suffer from a version of the inverse inference problem. The only known solution to the inverse inference problem is to use the famous theorem by Bayes, but this involves commitments that many researchers are not willing to make. However, it is possible to ask a useful question for which inverse inference is not a problem and that leads to the computation of the coefficient of confidence. In turn, and much more important, using the coefficient of confidence implies the desirability of switching from the current emphasis on a posteriori inferential statistics to an emphasis on a priori inferential statistics.
机译:>在零假设意义测试程序上有很大的争议,其中大部分批评都以反向推断的问题为中心。具体而言,<斜视> P 给出了零假设的查找(或一个更极端)的概率,而无效假设意义测试程序涉及给出发现的零假设的结论。许多批评者要求用置信区间替换为零假假设意义测试。然而,置信区间也遭受反向推理问题的一个版本。唯一已知的反向推理问题的解决方案是通过贝叶斯使用着名的定理,但这涉及许多研究人员不愿意制造的承诺。然而,可以提出一个有用的问题,其中逆推论不是问题,并且导致对置信系数的计算。反过来又重要,利用置信系数意味着从当前强调切换到后验统计的可取性,以强调先前推理统计。

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