Performs an F test to compare the variances of two samples from normal populations.

`var.test(x, …)`# 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, …)

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`

and `y`

.

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`

where `lhs`

is a numeric variable giving the data values and `rhs`

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
formula `formula`

. By default the variables are taken from
`environment(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 to
`getOption("na.action")`

.

…

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 `x`

and
`y`

.

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 `x`

and `y`

were drawn, or in the
data to which the linear models `x`

and `y`

were fitted, is
equal to `ratio`

.

`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.

# NOT RUN { 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. # }