| mood.test {stats} | R Documentation | 
Performs Mood's two-sample test for a difference in scale parameters.
mood.test(x, ...)
## Default S3 method:
mood.test(x, y, alternative = c("two.sided", "less", "greater"), ...)
## S3 method for class 'formula':
mood.test(formula, data, subset, na.action, ...)
x, y | 
numeric vectors of data values. | 
alternative | 
indicates the alternative hypothesis and must be
one of "two.sided" (default), "greater" or
"less" all of which can be abbreviated. | 
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 NAs.  Defaults to
getOption("na.action"). | 
... | 
further arguments to be passed to or from methods. | 
The underlying model is that the two samples are drawn from f(x-l) and f((x-l)/s)/s, respectively, where l is a common location parameter and s is a scale parameter.
The null hypothesis is s = 1.
There are more useful tests for this problem.
A list with class "htest" containing the following components:
statistic | 
the value of the test statistic. | 
p.value | 
the p-value of the test. | 
alternative | 
a character string describing the alternative hypothesis. | 
method | 
the character string "Mood two-sample test of scale". | 
data.name | 
a character string giving the names of the data. | 
William J. Conover (1971), Practical nonparametric statistics. New York: John Wiley & Sons. Pages 234f.
fligner.test for a rank-based (nonparametric) k-sample
test for homogeneity of variances;
ansari.test for another rank-based two-sample test for a
difference in scale parameters;
var.test and bartlett.test for parametric
tests for the homogeneity in variance.
## Same data as for the Ansari-Bradley test:
## Serum iron determination using Hyland control sera
ramsay <- c(111, 107, 100, 99, 102, 106, 109, 108, 104, 99,
            101, 96, 97, 102, 107, 113, 116, 113, 110, 98)
jung.parekh <- c(107, 108, 106, 98, 105, 103, 110, 105, 104,
            100, 96, 108, 103, 104, 114, 114, 113, 108, 106, 99)
mood.test(ramsay, jung.parekh)
## Compare this to ansari.test(ramsay, jung.parekh)