October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Content preview from 数据科学中的实用统计学(第2版)
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80
｜
第
3
章
3.2.4
扩展阅读
• Leonard Mlodinow
的著作
The Drunkard’s Walk
中对“随机性控制我们生活”的方式进行
了通俗易懂的阐述。
• David Freedman
、
Robert
Pisani
和
Roger Purves
的经典统计学教科书
Statistics
第
4
版，
对多数统计学问题进行了精彩讲述，并且没有涉及太多数学理论，其中就包括假设检验。
• Peter Bruce
在其著作
Introductory Statistics and Analytics:
A Resampling Perspective
中，使
用重抽样方法实现了假设检验。
3.3
重抽样
统计学中的
重抽样
就是反复地从观测数据中抽取数据值，它的目标是评估一个统计量中的
随机变异性。重抽样还可以用来评估和提高某些机器学习模型的准确度（例如，建立在多
个自助抽样数据集上的决策树模型的预测结果，可以通过一个称为
装袋
的过程进行平均，
参见
6.3
节
）。
两种主要的重抽样过程是
Bootstrap
和
置换检验
。前一章已经讨论过了，
Bootstrap
用来评
估一个估计的可靠性（参见
2.4
节）
。置换检验用来对假设进行检验，它通常包括两个或多
个组，这一节将对其进行讨论。
本节关键术语
置换检验
将两个或多个样本组合在一起，并随机地（或彻底地）将观测重新分配给重抽样的
过程。
同义词
随机化检验、随机置换检验、准确检验
重抽样
从一个观测数据集中再次抽取出一个样本（“重抽样”）。
有放回和无放回
在抽样过程中，如果抽出的项目在下一次抽取之前放回到样本中，就是有放回，否 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.