How to compute P-value and standard error from correlation analysis of R's cor()

Question

I have data that contain 54 samples for each condition (x and y). I have computed the correlation the following way:

> dat <- read.table(\"http://dpaste.co         


        

Answer 1

Can't you simply take the test statistic from the return value? Of course the test statistic is the estimate/se so you can calc se from just dividing the estimate by the tstat:

Using mydf in the answer above:

r = cor.test(mydf$X, mydf$Y)
tstat = r$statistic
estimate = r$estimate
estimate; tstat

       cor 
-0.8492663 
        t 
-5.086732