cor.test {ctest} | R Documentation |
cor.test
tests the null that x
and y
are
uncorrelated (independent).
cor.test(x, y, alternative = "two.sided", method = "pearson", exact = NULL)
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. |
exact |
a logical indicating whether an exact p-value should be computed. |
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
necessarily come from a bivariate normal distribution.
For Kendall's test, by default (if exact
is not specified), an
exact p-value is computed if both samples contain less than 50 finite
values and there are no ties. Otherwise, the standardized estimate is
used as the test statistic, and is approximately normally distributed.
For Spearman's test, p-values are computed using algorithm AS 89.
"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. |
D. J. Best & D. E. Roberts (1975), Algorithm AS 89: The Upper Tail Probabilities of Spearman's rho. Applied Statistics, 24, 377379.