Hi, I understand that to test the significance of correlation between two PAIRED variables, the function, cor.test () can be used. However, in my case, I have tested the correlation (i.e., Correlation Coefficient, r) between two independent (i.e, different) variables, and now I wish to test for the statistical significance of the correlation. Could you please suggest how I should do that. Thank you. Kind regards, Chintanu [[alternative HTML version deleted]]
If you have pearson correlation coefficients r calculated from n data points
elsewhere, you can use a t test on
t.r <- r * sqrt( (n-2)/(1-r^2) )
You'll need to use pt() to get your p value from t.r, though.
S Ellison
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I understand that to test the significance of correlation between two
PAIRED variables, the function, cor.test () can be used. However, in my
case, I have tested the correlation (i.e., Correlation Coefficient, r)
between two independent (i.e, different) variables, and now I wish to test
for the statistical significance of the correlation. Could you please
suggest how I should do that.
Thank you.
Kind regards,
Chintanu
[[alternative HTML version deleted]]
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On 31/07/12 21:13, Chintanu wrote:> Hi, > > I understand that to test the significance of correlation between two > PAIRED variables, the function, cor.test () can be used. However, in my > case, I have tested the correlation (i.e., Correlation Coefficient, r) > between two independent (i.e, different) variables, and now I wish to test > for the statistical significance of the correlation. Could you please > suggest how I should do that.In a word, don't. If two random variables are independent then they are necessarily (and obviously) uncorrelated. Note that "independent" is not synonymous with "different". cheers, Rolf Turner