I have grouped data, for which I would like to test several basic inference statistics.
library(tidyverse)
df <- data.frame(x=runif(50, min = 0, max = 25),y=runif(50, min = 10, max = 25), group=rep(0:1,25))
df %>%
group_by(group) %>%
summarize(cor(x,y))
Here I can easily get the correlation, but I also need to check it's statistical significance. Unfortunately options like cor.test
does not work in dyplr
. Is there an easy workaround?
Could this be what you want?
df %>%
group_by(group) %>%
summarize(cor.test(x,y)[["p.value"]])
The thing is that cor.test()
returns a list and not a single value, so you need to pick the element out of the list that you are interested in.