Performs an F test to compare the variances of two samples from normal populations.
# S3 method for default var.test(x, y, ratio = 1, alternative = c("two.sided", "less", "greater"), conf.level = 0.95, …)
# S3 method for formula var.test(formula, data, subset, na.action, …)
numeric vectors of data values, or fitted linear model
objects (inheriting from class
the hypothesized ratio of the population variances of
a character string specifying the alternative
hypothesis, must be one of
"less". You can specify just the initial
confidence level for the returned confidence interval.
a formula of the form
lhs ~ rhs where
is a numeric variable giving the data values and
rhs a factor
with two levels giving the corresponding groups.
an optional matrix or data frame (or similar: see
model.frame) containing the variables in the
formula. By default the variables are taken from
an optional vector specifying a subset of observations to be used.
a function which indicates what should happen when
the data contain
NAs. Defaults to
further arguments to be passed to or from methods.
A list with class
"htest" containing the following components:
the value of the F test statistic.
the degrees of the freedom of the F distribution of the test statistic.
the p-value of the test.
a confidence interval for the ratio of the population variances.
the ratio of the sample variances of
the ratio of population variances under the null.
a character string describing the alternative hypothesis.
the character string
"F test to compare two variances".
a character string giving the names of the data.
The null hypothesis is that the ratio of the variances of the
populations from which
y were drawn, or in the
data to which the linear models
y were fitted, is
bartlett.test for testing homogeneity of variances in
more than two samples from normal distributions;
mood.test for two rank
based (nonparametric) two-sample tests for difference in scale.