# mood.test

##### Mood Two-Sample Test of Scale

Performs Mood's two-sample test for a difference in scale parameters.

- Keywords
- htest

##### Usage

`mood.test(x, ...)`## S3 method for class 'default':
mood.test(x, y,
alternative = c("two.sided", "less", "greater"), ...)

## S3 method for class 'formula':
mood.test(formula, data, subset, na.action, \dots)

##### Arguments

- 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
`NA`

s. Defaults to`getOption("na.action")`

. - ...
- further arguments to be passed to or from methods.

##### Details

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.

In the case of ties, the formulation of Mielke (1967) is employed.

##### Value

- 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. You can specify just the initial letter. method the character string `"Mood two-sample test of scale"`

.data.name a character string giving the names of the data.

##### References

William J. Conover (1971),
*Practical nonparametric statistics*.
New York: John Wiley & Sons.
Pages 234f.

Paul W. Mielke, Jr. (1967),
Note on some squared rank tests with existing ties.
*Technometrics*, **9**/2, 312--314.

##### See Also

`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.

##### Examples

`library(stats)`

```
## 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)
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*