如何在R中使用資料框中的因子列執行配對t檢驗?
當我們在R資料框中有一個具有兩個水平的因子列和一個數值列時,我們可以對該資料框應用配對t檢驗,但資料必須是針對同一物件收集的,否則它就不是配對資料。此處討論的資料的t.test應用可以使用命令t.test(y1~x1,data=df)完成,其中y1是數值列,x1是因子列,這兩個列都儲存在名為df的資料框中。
示例
考慮以下資料框:
x1<-sample(c("Male","Female"),20,replace=TRUE)
y1<-rpois(20,5)
df1<-data.frame(x1,y1)
df1輸出
x1 y1 1 Female 4 2 Male 4 3 Female 4 4 Male 4 5 Female 6 6 Male 4 7 Female 3 8 Male 4 9 Female 7 10 Male 6 11 Male 2 12 Female 1 13 Male 5 14 Male 8 15 Male 6 16 Male 6 17 Female 3 18 Female 5 19 Male 4 20 Male 5
對df1中的資料應用t.test:
示例
t.test(y1~x1,data=df1)
輸出
Welch Two Sample t-test data: y1 by x1 t = -0.88636, df = 12.897, p-value = 0.3917 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -2.436194 1.019527 sample estimates: mean in group Female mean in group Male 4.125000 4.833333
示例
x2<-sample(c("Hot","Cold"),20,replace=TRUE)
y2<-sample(0:9,20,replace=TRUE)
df2<-data.frame(x2,y2)
df2輸出
x2 y2 1 Hot 8 2 Cold 1 3 Hot 5 4 Hot 2 5 Cold 4 6 Cold 0 7 Hot 8 8 Cold 3 9 Cold 9 10 Cold 6 11 Cold 0 12 Cold 9 13 Hot 6 14 Hot 2 15 Cold 3 16 Hot 1 17 Cold 6 18 Hot 7 19 Hot 8 20 Hot 9
對df2中的資料應用t.test:
示例
t.test(y2~x2,data=df2)
輸出
Welch Two Sample t-test data: y2 by x2 t = -1.0627, df = 17.721, p-value = 0.3022 alternative hypothesis: true difference in means is not equal to 0 95 percent confidence interval: -4.46872 1.46872 sample estimates: mean in group Cold mean in group Hot 4.1 5.6
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