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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.