correlation_test
              Perform a correlation coefficient test whether two samples x and y come from uncorrelated populations.
 h = correlation_test (y, x) tests the null
 hypothesis that the two samples x and y come from uncorrelated
 populations.  The result is h = 0 if the null hypothesis cannot be
 rejected at the 5% significance level, or h = 1 if the null hypothesis
 can be rejected at the 5% level.  y and x must be vectors of
 equal length with finite real numbers.
The p-value of the test is returned in pval. stats is a structure with the following fields:
| Field | Value | ||
|---|---|---|---|
| method | the type of correlation coefficient used for the test | ||
| df | the degrees of freedom (where applicable) | ||
| corrcoef | the correlation coefficient | ||
| stat | the test’s statistic | ||
| dist | the respective distribution for the test | ||
| alt | the alternative hypothesis for the test | 
 […] = correlation_test (…, name, value)
 specifies one or more of the following name/value pairs:
| Name | Value | |
|---|---|---|
| "alpha" | the significance level. Default is 0.05. | |
| "tail" | a string specifying the alternative hypothesis | 
| "both" | is not 0 (two-tailed, default) | |
| "left" | is less than 0 (left-tailed) | |
| "right" | is greater than 0 (right-tailed) | 
| "method" | a string specifying the correlation coefficient used for the test | 
| "pearson" | Pearson’s product moment correlation (Default) | |
| "kendall" | Kendall’s rank correlation tau | |
| "spearman" | Spearman’s rank correlation rho | 
See also: regression_ftest, regression_ttest
Source Code: correlation_test