var.test
F Test to Compare Two Variances
Performs an F test to compare the variances of two samples from normal populations.
 Keywords
 htest
Usage
var.test(x, ...)
"var.test"(x, y, ratio = 1, alternative = c("two.sided", "less", "greater"), conf.level = 0.95, ...)
"var.test"(formula, data, subset, na.action, ...)
Arguments
 x, y
 numeric vectors of data values, or fitted linear model
objects (inheriting from class
"lm"
).  ratio
 the hypothesized ratio of the population variances of
x
andy
.  alternative
 a character string specifying the alternative
hypothesis, must be one of
"two.sided"
(default),"greater"
or"less"
. You can specify just the initial letter.  conf.level
 confidence level for the returned confidence interval.
 formula
 a formula of the form
lhs ~ rhs
wherelhs
is a numeric variable giving the data values andrhs
a factor with two levels giving the corresponding groups.  data
 an optional matrix or data frame (or similar: see
model.frame
) containing the variables in the formulaformula
. By default the variables are taken fromenvironment(formula)
.  subset
 an optional vector specifying a subset of observations to be used.
 na.action
 a function which indicates what should happen when
the data contain
NA
s. Defaults togetOption("na.action")
.  ...
 further arguments to be passed to or from methods.
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
 statistic
 the value of the F test statistic.
 parameter
 the degrees of the freedom of the F distribution of the test statistic.
 p.value
 the pvalue of the test.
 conf.int
 a confidence interval for the ratio of the population variances.
 estimate
 the ratio of the sample variances of
x
andy
.  null.value
 the ratio of population variances under the null.
 alternative
 a character string describing the alternative hypothesis.
 method
 the character string
"F test to compare two variances"
.  data.name
 a character string giving the names of the data.
"htest"
containing the following components:
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) twosample tests for difference in scale.
Examples
library(stats)
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.
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