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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102
｜
第
3
章
r
×
c
表示行数乘以列数——一个
2
×
3
的表格有
2
行
3
列。
3.9.1
卡方检验
：
一种重抽样方法
假设你要测试三个不同的标题——
A
、
B
和
C
。你对每个标题都使用
1000
名访问者进行了
测试，结果如表
3-4
所示。
表3-4：三个标题的Web测试结果
标题A 标题B 标题C
点击
14 8 12
没有点击
986 992 988
这些标题看上去差异明显，标题
A
的点击率差不多是标题
B
的两倍，不过，实际数值有
点儿小了。重抽样可以检验这些点击率之间的差异是否超过了随机因素的影响范围。要进
行这种检验，我们需要一种点击的“预期”分布。在这个例子中，零假设认为这三个标题
具有同样的点击率，即总体点击率为
34/3000
，而预期分布就是建立在这个零假设之上的
。
根据零假设，点击率的列联表应该类似于表
3-5
。
表3-5：三个标题具有相同点击率（零假设）时的预期分布
标题A 标题B 标题C
点击
11.33 11.33 11.33
没有点击
988.67 988.67 988.67
皮尔逊残差
定义如下：
预期值
R
−
=
观测 预值 期值
R
测量的是实际计数与预期计数之间的差异程度（见表
3-6
）。
表3-6：皮尔逊残差
标题A 标题B 标题C
点击
0.792 –0.990 0.198
没有点击
–0.085 0.106 –0.021
卡方统计量就定义为皮尔逊残差的平方和：
2
rc
ij
XR=
∑∑
统计实验与显著性检验
｜
103
其中
r
和
c
分别是行数和列数。本例中卡方统计量的值是
1.666
。它是否超出了随机模型结
果的合理范围？ ...
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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.