VarTest: ChiSquare Test for One Variance and F Test to Compare Two Variances

Description

Performs either a one sample ChiSquare test to compare the variance of a vector with a given value or an F test to compare the variances of two samples from normal populations.

Usage

VarTest(x, ...)
"VarTest"(x, y, alternative = c("two.sided", "less", "greater"), ratio = 1, sigma.squared = 1, conf.level = 0.95, ...)
"VarTest"(formula, data, subset, na.action, ...)

Arguments

x, y

numeric vectors of data values.

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.

ratio

the hypothesized ratio of the population variances of x and y.

sigma.squared

a number indicating the true value of the variance, if one sample test is requested.

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 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.

Value

A list with class "htest" containing the following components:

Details

The formula interface is only applicable for the 2-sample tests.

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.

Examples

Run this code

x <- rnorm(50, mean = 0, sd = 2)

# One sample test
VarTest(x, sigma.squared = 2.5)

# two samples
y <- rnorm(30, mean = 1, sd = 1)
VarTest(x, y)                  # Do x and y have the same variance?
VarTest(lm(x ~ 1), lm(y ~ 1))  # The same.

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