RcmdrPlugin.TeachStat (version 1.1.0)

VUM.test: Chi-square test for the variance of a Normal variable with unknown population mean.

Description

Under the assumption that the data come from a Normal distribution, it performs the hypothesis testing and the confidence interval for the variance with unknown population mean.

Usage

VUM.test(x, sigma = 1, sigmasq = sigma^2,
         alternative = c("two.sided", "less", "greater"), conf.level = 0.95,
         ...)

Arguments

x

a (non-empty) numeric vector of data values.

sigma

a number indicating the true value of the population standar deviation - Null hypothesis.

sigmasq

control argument.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided", "greater" o "less". You can specify just the initial letter.

conf.level

confidence level of the interval.

…

further arguments to be passed to or from methods.

Value

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

statistic

the value of the test statistic

parameter

the degrees of freedom for the test statistic

p.value

the p-value for the test.

conf.int

confidence interval for variance with unknown population mean associated with the specified alternative hypothesis.

estimate

vthe estimated variance.

null.value

the specified hypothesized value of the variance.

alternative

a character string describing the alternative hypothesis.

method

a character string indicating what type of statistical test was performed.

data.name

a character string giving the name of the data.

See Also

VKM.test , var.test

Examples

# NOT RUN {
data(cars93) # Dataset provided with the package
# Variance of the maximum price (MaxPrice) assuming that the population mean 
# price is unknown
VUM.test(cars93$MaxPrice, alternative="two.sided", sigma=11, conf.level=0.95)
# }