Just stating the obvious that Peter left unsaid: The OP calculated a
matrix, whose diagonal is the correlations between each variable and
itself, with the off-diagonal entries being the ones of interest.
On 17-May-13, at 11:06 AM, Peter Ehlers wrote:
On 2013-05-17 08:37, Jose Iparraguirre wrote:
Dear Elaine,
One of the elements you obtain the P matrix, which is the matrix
of asymptotic p-values. In your case, you get that the asymptotic
p-value of the association between t_i and t_r is 0. That is,
there would exist a perfect association (look also at the first
result, the matrix of correlations: the correlation coefficient
between these variables is 1).
Hope this helps,
José
Actually, the coefficient is -0.89.
Not surprisingly, with n = 4873, this indicates a significant
correlation.
For details of the t-test involved in the calculation, see any
intro stats text or look at the code of cor.test.default().
Peter Ehlers
Prof. José Iparraguirre
Chief Economist
Age UK
-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of Elaine Kuo
Sent: 17 May 2013 10:40
To: r-help@r-project.org
Subject: [R] pearson correlation significant level
Hello
I am using package Hmisc to calculate the pearson correlation and
the significant level for the matrix of t_i and t_r. (temperature
minimum and temperature range)
However, I have difficulty interpreting the result, even after
checking the manual.
Please kindly help to indicate if the p-value is zero.
Thank you in advance.
Elaine
The code
library(Hmisc)
rcorr(as.matrix(datat), type="pearson") # type can be pearson or
spearman
The result is
t_i t_r
t_i 1.00 -0.89
t_r -0.89 1.00
n= 4873
P
t_i t_r
t_i 0
t_r 0
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