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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探索性数据分析
｜
29
著下跌而另一种股票上涨，或者反过来（第二象限和第四象限中的点）。
尽管图
1-7
中只显示了
754
个数据点
，但明显可以看出，我们很难在图形中部识别出更加
详细的信息。稍后将介绍如何为数据点添加透明度，或使用六边形分箱图和密度图，来帮
助你发现数据中的其他结构。
本节要点
•
相关系数测量的是两个成对变量（如人的身高和体重）之间关联的程度。
•
当
v1
值随着
v2
值的增大而增大时，
v1
和
v2
正相关。
•
当
v1
值随着
v2
值的增大而减小时，
v1
和
v2
负相关。
•
相关系数是一种标准化的度量方式，所以它的值总是在
–1
（完全负相关）和
+1
（完
全正相关）之间。
•
相关系数为
0
表示没有相关性，但是请注意，如果对数据进行随机重新排列，则既
可能得到正相关系数，又可能得到负相关系数，这是由偶然性造成的。
1.7.2
扩展阅读
David Freedman
、
Robert Pisani
和
Roger Purves
的著作
Statistics
（第
4
版）对相关性进行了
精彩的讨论。
1.8
探索两个及以上的变量
像均值和方差这些我们熟悉的估计量每次只研究一个变量（
单变量分析
），而相关性分析
（见
1.7
节
）是比较两个变量的重要方法（
双变量分析
）。这一节介绍一些其他的估计方法
和绘图方式，将涉及两个以上的变量（
多变量分析
）。
本节关键术语
列联表
一种表格，包含对两个或更多的分类变量的计数。
六边形分箱图
一种包含两个数值变量的统计图，记录分成多个六边形箱子。
等高线图
一种表示两个数值变量的密度的统计图，类似于地形图。
小提琴图
类似于箱线图，但能表示出密度估计。 ...
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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.