Applied Nonparametric Statistics-lec9

Ref:https://onlinecourses.science.psu.edu/stat464/print/book/export/html/12



前面我们考虑的情况是:response是连续的,variable是离散的。举例:如果打算检查GPA的中位数是否与学生坐在教室的位置有关,

那么GPA的中位数是连续的,是响应变量;学生坐的位置(前中后)是离散的,是解释变量。

现在考虑解释变量也是连续的情况,即检查两个连续变量之间的因果关系。其中,我们最关心的是关系的强弱和方向。

首先,我们考虑线性相关的情况,计算Pearson‘s correlation coefficient

计算Pearson‘s Correlation Coefficient

cor.test(x, y)

结果将给出系数cor,置信区间,p-value

计算斜率(最小二乘法拟合时)

> h=c(67, 62, 64, 65)
> w=c(120, 172, 167, 145)
> lm(w~h)

注意:这里使用的是y~x来拟合,应该是可以选用不同的公式的。结果里,斜率是-10.85



Spearman‘s Rank Correlation

使用两个变量的rank值,置换计算Pearson‘s,就是Spearman‘s

Kendall‘s Tau Rank Correlation

measuring association by counting the number of concordant and disconcordant pairs

concordant pairs

时间: 2024-11-08 18:57:32

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