c*1
2 楼
查了一下这架飞机经济舱有72个座位。据说被randomly chosen的4个人有3个是亚裔,
如果这是真的,那么做一个chi-sq test就知道有没有歧视了。
假设72个人有17个亚裔
[,1] [,2]
[1,] 54 14
[2,] 1 3
p-value = 0.0595
假设72个人有16个亚裔
[,1] [,2]
[1,] 55 13
[2,] 1 3
p-value = 0.04617
也就是说在95%信心水平下,如果72个人中亚裔少于17个,就可以说踢人的过程中存在
歧视
如果这是真的,那么做一个chi-sq test就知道有没有歧视了。
假设72个人有17个亚裔
[,1] [,2]
[1,] 54 14
[2,] 1 3
p-value = 0.0595
假设72个人有16个亚裔
[,1] [,2]
[1,] 55 13
[2,] 1 3
p-value = 0.04617
也就是说在95%信心水平下,如果72个人中亚裔少于17个,就可以说踢人的过程中存在
歧视
p*r
3 楼
what's the point??
s*d
5 楼
今天是上周五的翻版。
w*p
6 楼
如果飞机上只有4个亚裔,p value是多少
K*2
8 楼
2 by 2 contingency table, 要用Fisher's exact test,超几何分布
K*2
10 楼
> x=matrix(c(54,1,14,3),ncol=2)
> fisher.test(x)
Fisher's Exact Test for Count Data
data: x
p-value = 0.03867
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8184615 615.7103837
sample estimates:
odds ratio
11.0593
> x=matrix(c(55,1,13,3),ncol=2)
> fisher.test(x)
Fisher's Exact Test for Count Data
data: x
p-value = 0.03225
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8907116 674.7945125
sample estimates:
odds ratio
12.08438
> fisher.test(x)
Fisher's Exact Test for Count Data
data: x
p-value = 0.03867
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8184615 615.7103837
sample estimates:
odds ratio
11.0593
> x=matrix(c(55,1,13,3),ncol=2)
> fisher.test(x)
Fisher's Exact Test for Count Data
data: x
p-value = 0.03225
alternative hypothesis: true odds ratio is not equal to 1
95 percent confidence interval:
0.8907116 674.7945125
sample estimates:
odds ratio
12.08438
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