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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统计实验与显著性检验
｜
91
3.5
t
检验
根据数据中是否包含计数数据或测量数据、数据中有多少个样本以及测量的对象，可以有
无数种显著性检验。
t
检验是其中一种非常常用的检验方法
，它的名称来自于最初由
W. S.
Gosset
提出的学生的
t
分布。
t
检验用来近似单样本均值的分布（参见
2.8
节
）。
本节关键术语
检验统计量
一种对我们所关注的差异或效果的度量方式。
t
统计量
常用检验统计量（如均值）的标准化版本。
t
分布
一种参照分布（这里是从零假设导出的），可以与观测到的
t
统计量进行比较。
所有显著性检验都需要指定一种
检验统计量
，用来测量所关注的效果，并帮助确定观测效
果是否位于正常的随机变动范围内。在重抽样检验（参见
3.3.1
节中对置换检验的讨论）
中，数据的规模并不重要。你可以根据数据本身创建参照（零假设）分布，然后使用相应
的检验统计量。
20
世纪二三十年代
，统计假设检验开始发展起来，当时还没有能力对数据进行成千上万
次的随机重排来实现重抽样检验。统计学家发现，基于
Gosset
的
t
分
布，
t
检验是对置换
（打乱重排）分布的一个很好的近似。
t
检验可以用于非常常见的两样本比较—
—
A/B
测
试，其中的数据是数值型的。但是，为了在使用
t
分布时无须考虑数据规模
，必须使用检
验统计量的标准化形式。
经典统计学教科书在介绍
t
检
验时，会给出各种包含了
Gosset
分布的公式，并演示如何对
数据进行标准化，以便与标准的
t
分布进行比较
。我们不使用那些公式，因为所有统计软
件（包括
R
和
Python
）都包含了能实现这些公式的命令。在
R
中，这个函数是 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
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.