R 两对t检验p值=NA和t=NaN

我想做以下配对t检验：

str1<-' ENSEMBLE 0.934 0.934 0.934 0.934 '
  str2<-' J48 0.934 0.934 0.934 0.934 '

  df1 <- read.table(text=scan(text=str1, what='', quiet=TRUE), header=TRUE)
  df2 <- read.table(text=scan(text=str2, what='', quiet=TRUE), header=TRUE)

t.test ( df1$ENSEMBLE, df2$J48, mu=0 , alt="two.sided", paired = T, conf.level = 0.95)

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为什么我会得到它？

这是因为数据集完全相同

df2[1,1] <- .935

t.test ( df1$ENSEMBLE, df2$J48, mu=0 , alt="two.sided", paired = T, conf.level = 0.95)

Paired t-test

data:  df1$ENSEMBLE and df2$J48
t = -1, df = 3, p-value = 0.391
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.0010456116  0.0005456116
sample estimates:
mean of the differences 
           -0.00025 

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df2[1,1]您的两个向量完全相同。两组均无差异，因此无标准误差。所以你的答案是不确定的

df2[1,1] <- .935

t.test ( df1$ENSEMBLE, df2$J48, mu=0 , alt="two.sided", paired = T, conf.level = 0.95)

Paired t-test

data:  df1$ENSEMBLE and df2$J48
t = -1, df = 3, p-value = 0.391
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.0010456116  0.0005456116
sample estimates:
mean of the differences 
           -0.00025