correlation_test
statistics: h = correlation_test (x, y)
statistics: [h, pval] = correlation_test (y, x)
statistics: [h, pval, stats] = correlation_test (y, x)
statistics: […] = correlation_test (y, x, Name, Value)
Perform a correlation coefficient test to determine 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 |
Source Code: correlation_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 |
Source Code: correlation_test
'both' | corrcoef is not 0 (two-tailed, default) |
'left' | corrcoef is less than 0 (left-tailed) |
'right' | corrcoef is greater than 0 (right-tailed) |
Source Code: correlation_test
'method' | a string specifying the correlation coefficient used for the test |
Source Code: correlation_test
'pearson' | Pearson’s product moment correlation (Default) |
'kendall' | Kendall’s rank correlation tau |
'spearman' | Spearman’s rank correlation rho |
Source Code: correlation_test
See also: regression_ftest, regression_ttest
Source Code: correlation_test