What Teachers Should Know about the Bootstrap: Resampling in the Undergraduate Statistics Curriculum

AMERICAN STATISTICIAN(2015)

引用 196|浏览21
暂无评分
摘要
Bootstrapping has enormous potential in statistics education and practice, but there are subtle issues and ways to go wrong. For example, the common combination of nonparametric bootstrapping and bootstrap percentile confidence intervals is less accurate than using t-intervals for small samples, though more accurate for larger samples. My goals in this article are to provide a deeper understanding of bootstrap methodshow they work, when they work or not, and which methods work betterand to highlight pedagogical issues. Supplementary materials for this article are available online.[Received December 2014. Revised August 2015]
更多
查看译文
关键词
Bias,Confidence intervals,Sampling distribution,Standard error,Statistical concepts,Teaching
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要