Division of Biostatistics and Bioinformatics, National Jewish Health, Denver, Colorado 80206, USA.
Adv Physiol Educ. 2012 Sep;36(3):181-7. doi: 10.1152/advan.00072.2012.
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eighth installment of Explorations in Statistics explores permutation methods, empiric procedures we can use to assess an experimental result-to test a null hypothesis-when we are reluctant to trust statistical theory alone. Permutation methods operate on the observations-the data-we get from an experiment. A permutation procedure answers this question: out of all the possible ways we can rearrange the observations we got, in what proportion of those arrangements is the sample statistic we care about at least as extreme as the one we got? The answer to that question is the P value.
如果您可以积极探索，学习会更有意义。本统计学探索系列的第八部分探讨了置换方法，这是我们在不愿意仅依赖统计理论时可以用来评估实验结果（即检验零假设）的经验程序。置换方法基于我们从实验中获得的观测值（数据）。置换程序回答了这个问题：在我们可以重新排列所得到的观测值的所有可能方式中，有多少种排列方式中，我们关心的样本统计量至少与我们得到的那个统计量一样极端？这个问题的答案就是 P 值。
