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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数据与抽样分布
｜
45
些相关记录，需要几万亿个数据点（随机抽样并不会提供什么帮助），参见
2.7
节。
2.1.4
样本均值与总体均值
我们使用符号
x
表示来自于总体的一个样本的均值，用
μ
表示总体均值。为什么要进行
这种区分呢？因为样本的相关信息是可以观测的，而大型总体的相关信息通常是根据小样
本推断出来的。统计学家一般通过符号表示对二者进行区分。
本节要点
•
即使在大数据时代，随机抽样仍然是数据科学家重要的工具。
•
当测量或观测因为不具有总体代表性而产生系统性误差时，就会出现偏差。
•
数据质量通常比数据数量更重要，而随机抽样可以减小偏差，提高数据质量。但如
果不进行随机抽样，这些操作的成本会非常高。
2.1.5
扩展阅读
•
在
Nigel G. Fielding
、
Raymond M. Lee
和
Grant Blank
编辑的
The SAGE Handbook of Online
Research Method
s
第
2
版中，
Ronald Fricker
撰写了“
Sampling Methods for Online Surveys
”
一章，对抽样过程进行了介绍，还概述了随机抽样的修正方法，这些方法通常用于需要
考虑成本或可行性的情况。
•
在
Capital Century
网站上，可以找到关于《文学文摘》民意调查失败的故事。
2.2
选择偏差
尤吉
•
贝拉说过：“如果你不知道在寻找什么，那就尽力去找，最后总会找到的。”
选择偏差指以一种能导致误导性或暂时性结论的方式，有选择性地去选取数据（可能是有
意识的，也可能是无意识的） ...
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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.