April 2021
Intermediate to advanced
210 pages
6h 3m
Chinese
Content preview from 数据驱动力：企业数据分析实战
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A/B
测试
｜
119
的效果当作实验效果（推出一个没有实际作用的功能）。简而言之，你会得到更多的假阴
性或假阳性结论。永远不要因为实验效果看上去不错而缩短实验时长。
然而，许多
A/B
测试供应商鼓励用户运行实验
，直到获得显著性结果。永远不要这样运行
测试！通过以
4
个
厂家为例，
Martin Goodson
说道：“一个用于
A/B
测试的软件的设计方式，
让人很自然地一路监控测试结果，只要一获得显著结果就停止实验。令人担忧的是，用这种
方式执行测试的话，
80%
的测试结果会是假阳性。
”（参见“
How Not To Run An A/B Test
”。）
一旦你已经增大了实验的样本容量，而且有把握不出现恶劣问题，最好的建议是，以
Ronco
（街舞）方式去运行测试
：“设定，然后忘却。”随着时间的推移监控样本容量，而
不是评估指标。
8.3
其他方法
下面简要介绍其他两种可代替
A/B
测试或
A/A
测试的简单方法。
8.3.1
多变量测试
前面只讨论了组对（双样本）测试，一个对照组和一个实验组（
A/B
）或另外一个对照组
（
A/A
）
。这种实验设计非常简单有效。但是，它们也存在一些缺点。回忆一下，在之前讨
论的奥巴马助选活动中，他们采用不同文字和图片测试了提交按钮。因为他们准备了
5
种
按钮文字和至少
6
种图片
，所以存在至少
30
种组合。按顺序测试所有组合意味着要花费
30
倍于单次
A/B
测试的时间。正是因为这个原因，有时会使用多变量测试。
这些测试也称为多变量测试或者因子测试，同时运行不同的变量组合（或“菜单”）。也就
是说，组
1
用户看到图片
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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.
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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.