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数据科学中的实用统计学(第2版)
book

数据科学中的实用统计学(第2版)

by Peter Bruce, Andrew Bruce, Peter Gedeck
October 2021
Intermediate to advanced
289 pages
8h 31m
Chinese
Posts & Telecom Press
Content preview from 数据科学中的实用统计学(第2版)
144
4
本节关键术语
标准化残差
残差除以残差的标准误差。
离群点
与其他数据(或预测结果)相距甚远的记录(或结果值)。
强影响值
一个值或一条记录,是否有这个值或记录会在回归方程中造成很大的差异。
杠杆值
单条记录对回归方程的影响程度。
同义词
帽子值(
hat-value
非正态残差
非正态分布的残差可能会使回归中的某些技术需求无效,但通常不在数据科学的考
虑范围之内。
异方差
某些结果的残差具有更高的方差(可能说明回归方程中缺少了某个预测变量)。
偏残差图
一种用来诊断的统计图,表示结果变量和某个预测变量之间的关系。
同义词
变量添加图
4.6.1
 离群点
一般说来,极端值也称为
离群点
,它是远离大多数其他观测的观测。正如在位置估计和变
异性估计中要处理异常值一样(参见
1.3
节和
1.4
节)
,在回归模型中,离群点也会带来
问题。在回归中,离群点是实际
y
值远离预测值的记录。可以通过
标准化残差
来发现离群
点,标准化残差就是残差除以残差的标准误差。
虽然没有统计理论去区分离群点和非离群点,但是关于某个观测距离大多数数据有多远才
能被视为离群点,有很多经验法则。例如,在箱线图中,离群点是那些距离箱体边界上方
和下方过远的数据点(参见
1.5.1
节)
,这里的“过远”是指“大于
1.5
倍四分位距”。在回
归中,一般使用标准化残差作为确定某个记录是否是离群点的度量。标准化残差可以解释
为“与回归线的距离是多少个标准误差”。
回归与预测
145
使用所有邮政编码为
98105
的金县房屋销售数据拟合一个回归。
R
中:
house_98105 <- ...
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Publisher Resources

ISBN: 9787115569028