Explorations in statistics: the bootstrap

被引:40
作者
Curran-Everett, Douglas [1 ,2 ,3 ]
机构
[1] Natl Jewish Hlth, Div Biostat & Bioinformat, Denver, CO 80206 USA
[2] Univ Colorado, Dept Biostat & Informat, Denver, CO 80202 USA
[3] Univ Colorado, Sch Med, Dept Physiol & Biophys, Denver, CO 80202 USA
关键词
Central Limit Theorem; R; sample mean; software; standard error; CONFIDENCE; INCREASES; EXERCISE;
D O I
10.1152/advan.00062.2009
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Curran-Everett D. Explorations in statistics: the bootstrap. Adv Physiol Educ 33: 286-292, 2009; doi: 10.1152/advan.00062.2009. Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This fourth installment of Explorations in Statistics explores the bootstrap. The bootstrap gives us an empirical approach to estimate the theoretical variability among possible values of a sample statistic such as the sample mean. The appeal of the bootstrap is that we can use it to make an inference about some experimental result when the statistical theory is uncertain or even unknown. We can also use the bootstrap to assess how well the statistical theory holds: that is, whether an inference we make from a hypothesis test or confidence interval is justified.
引用
收藏
页码:286 / 292
页数:7
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