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)
我得到以下结果:
Paired t-test data: df1$ENSEMBLE and df2$J48 t = NaN, df = 3, p-value = NA alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: NaN NaN sample estimates: mean of the differences 0
我为什么要这个?
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