# [R] pearson correlation significant level

Peter Ehlers ehlers at ucalgary.ca
Fri May 17 20:06:50 CEST 2013

```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-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Elaine Kuo
> Sent: 17 May 2013 10:40
> To: r-help at 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.
> 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
>>
>>
>
> 	[[alternative HTML version deleted]]
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