cor.test(x, y, alternative = "two.sided", method = "pearson")
x, y
|
numeric vectors of data values. x and y
must have the same length.
|
alternative
|
indicates the alternative hypothesis and must be
one of "two.sided" , "greater" or "less" . You
can specify just the initial letter.
|
method
|
a string indicating which correlation coefficient is
used for the test. Must be one of "pearson" ,
"kendall" , or "spearman" . Only the first character is
necessary.
|
cor.test
tests the null that x
and y
are
uncorrelated.
If method
is "pearson"
, the test statistic is based on
Pearson's product moment correlation coefficient cor(x, y)
and
follows a t distribution with length(x)-2
degrees of freedom.
If method
is "kendall"
or "spearman"
, Kendall's
tau or Spearman's rho, respectively, are used to estimate the
correlation. These tests should be used if the data do not necessary
come from a bivariate normal distribution. In both cases, the
standardized estimate is used as the test statistic, and is
approximately normally distributed.
"htest"
containing the following components:
statistic
| the value of the test statistic. |
parameter
| the degrees of freedom of the test statistic in the case that it follows a t distribution. |
p.value
| the p-value of the test. |
estimate
|
the estimated correlation coefficient, with names
attribute "cor" , "tau" , or "rho" , correspoding
to the method employed.
|
null.value
|
the value of the correlation coefficient under the
null hypothesis, hence 0 .
|
alternative
| a character string describing the alternative hypothesis. |
method
| a string indicating how the correlation was estimated |
data.name
| a character string giving the names of the data. |