| var.test {ctest} | R Documentation |
F Test to Compare Two Variances
Description
Performs an F test to compare the variances of two samples from normal populations.
Usage
var.test(x, y, ratio = 1, alternative = c("two.sided", "less", "greater"),
conf.level = 0.95)
Arguments
x, y |
numeric vectors of data values, or fitted linear model
objects (inheriting from class |
ratio |
the hypothesized ratio of the population variances of
|
alternative |
the alternative hypothesis; must be one of
|
conf.level |
confidence level for the returned confidence interval. |
Details
The null hypothesis is that the ratio of the variances of the
populations from which x and y were drawn, or in the
data to which the linear models x and y were fitted, is
equal to ratio.
Value
A list with class "htest" containing the following components:
statistic |
the value of the F test statistic. |
parameter |
the degrees of the freedom of the F distribtion of the test statistic. |
p.value |
the p-value of the test. |
conf.int |
a confidence interval for the ratio of the population variances. |
estimate |
the ratio of the sample variances of |
null.value |
the ratio of population variances under the null. |
alternative |
a character string describing the alternative hypothesis. |
method |
the string |
data.name |
a character string giving the names of the data. |
See Also
bartlett.test for testing homogeneity of variances in
more than two samples from normal distributions;
ansari.test and mood.test for two rank
based (nonparametric) two-sample tests for difference in scale.
Examples
x <- rnorm(50, mean = 0, sd = 2)
y <- rnorm(30, mean = 1, sd = 1)
var.test(x, y) # Do x and y have the same variance?
var.test(lm(x ~ 1), lm(y ~ 1)) # The same.