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Last data update: 2014.03.03

R: Test for outlying or inlying variance

cochran.test

R Documentation

Test for outlying or inlying variance

Description

This test is useful to check if largest variance in several groups of data is "outlying" and this group should be rejected. Alternatively, if one group has very small variance, we can test for "inlying" variance.

Usage

cochran.test(object, data, inlying = FALSE)

Arguments

`object`	A vector of variances or formula.
`data`	If object is a vector, data should be another vector, giving number of data in each corresponding group. If object is a formula, data should be a dataframe.
`inlying`	Test smallest variance instead of largest.

Details

The corresponding p-value is calculated using pcochran function.

Value

A list with class htest containing the following components:

`statistic`	the value of Cochran-statistic.
`p.value`	the p-value for the test.
`alternative`	a character string describing the alternative hypothesis.
`method`	a character string indicating what type of test was performed.
`data.name`	name of the data argument.
`estimate`	vector of variance estimates

Author(s)

Lukasz Komsta

References

Snedecor, G.W., Cochran, W.G. (1980). Statistical Methods (seventh edition). Iowa State University Press, Ames, Iowa.

Examples

set.seed(1234)
x=rnorm(100)
d=data.frame(x=x,group=rep(1:10,10))
cochran.test(x~group,d)
cochran.test(x~group,d,inlying=TRUE)
x=runif(5)
cochran.test(x,rep(5,5))
cochran.test(x,rep(100,5))