| var.test {stats} | R Documentation |
Performs an F test to compare the variances of two samples from normal populations.
var.test(x, ...)
## Default S3 method:
var.test(x, y, ratio = 1,
alternative = c("two.sided", "less", "greater"),
conf.level = 0.95, ...)
## S3 method for class '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 data frame containing the variables in the model 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 NAs. Defaults to
getOption("na.action"). |
... |
further arguments to be passed to or from methods. |
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.
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 x and
y. |
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. |
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.
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.