bartlett.test
Bartlett Test of Homogeneity of Variances
Performs Bartlett's test of the null that the variances in each of the groups (samples) are the same.
 Keywords
 htest
Usage
bartlett.test(x, ...)
"bartlett.test"(x, g, ...)
"bartlett.test"(formula, data, subset, na.action, ...)
Arguments
 x
 a numeric vector of data values, or a list of numeric data
vectors representing the respective samples, or fitted linear model
objects (inheriting from class
"lm"
).  g
 a vector or factor object giving the group for the
corresponding elements of
x
. Ignored ifx
is a list.  formula
 a formula of the form
lhs ~ rhs
wherelhs
gives the data values andrhs
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
If x
is a list, its elements are taken as the samples or fitted
linear models to be compared for homogeneity of variances. In this
case, the elements must either all be numeric data vectors or fitted
linear model objects, g
is ignored, and one can simply use
bartlett.test(x)
to perform the test. If the samples are not
yet contained in a list, use bartlett.test(list(x, ...))
.
Otherwise, x
must be a numeric data vector, and g
must
be a vector or factor object of the same length as x
giving the
group for the corresponding elements of x
.
Value

A list of class
 statistic
 Bartlett's Ksquared test statistic.
 parameter
 the degrees of freedom of the approximate chisquared distribution of the test statistic.
 p.value
 the pvalue of the test.
 method
 the character string
"Bartlett test of homogeneity of variances"
.  data.name
 a character string giving the names of the data.
"htest"
containing the following components:
References
Bartlett, M. S. (1937). Properties of sufficiency and statistical tests. Proceedings of the Royal Society of London Series A 160, 268282.
See Also
var.test
for the special case of comparing variances in
two samples from normal distributions;
fligner.test
for a rankbased (nonparametric)
$k$sample test for homogeneity of variances;
ansari.test
and mood.test
for two rank
based twosample tests for difference in scale.
Examples
library(stats)
require(graphics)
plot(count ~ spray, data = InsectSprays)
bartlett.test(InsectSprays$count, InsectSprays$spray)
bartlett.test(count ~ spray, data = InsectSprays)