sigma.test | R Documentation |
Compute the test of hypothesis and compute a confidence interval on the variance of a population.
sigma.test(x, sigma = 1, sigmasq = sigma^2,
alternative = c("two.sided", "less", "greater"), conf.level = 0.95, ...)
x |
Vector of data values. |
sigma |
Hypothesized standard deviation of the population. |
sigmasq |
Hypothesized variance of the population. |
alternative |
Direction of the alternative hypothesis. |
conf.level |
Confidence level for the interval computation. |
... |
Additional arguments are silently ignored. |
Many introductory statistical texts discuss inference on a single
population variance and introduce the chi-square test for a population
variance as another example of a hypothesis test that can be easily
derived. Most statistical packages do not include the chi-square
test, perhaps because it is not used in practice very often, or
because the test is known to be highly sensitive to nonnormal
data. For the two-sample problem, see var.test
.
An object of class htest
containing the results
This test is highly sensitive to nonnormality.
G. Jay Kerns gkerns@ysu.edu
var.test
, print.htest
x <- rnorm(20, mean = 15, sd = 7)
sigma.test(x, sigma = 6)
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