z.test: Mean test using vector

In fhernanb/stests: Package with useful statistical tests

Mean test using vector

Description

This function performs the mean test using raw data (vector).

Usage

z.test(x, sigma2, alternative = "two.sided", mu = 0, conf.level = 0.95)

Arguments

x	a (non-empty) numeric vector of data values.
sigma2	population variance which is known.
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.
mu	the hypothesized number in the null hypothesis.
conf.level	confidence level of the interval, by default its value is 0.95.

Value

A list with class htest containing the following components:

statistic	the value of the statistic.
p.value	the p-value for the test.
conf.int	a confidence interval for the variance.
estimate	the estimated mean.
null.value	the specified hypothesized value for alternative hypothesis.
alternative	a character string describing the alternative hypothesis.
method	a character string indicating the type of test performed.
data.name	a character string giving the name of the data.

Examples

# Example 1
# H0: mu = 350
# Ha: mu < 350 with sigma2=25
content <- c(355, 353, 352, 346, 345, 345, 353, 353, 344, 350)
res1 <- z.test(x=content, mu=350, sigma2=25, alternative='less')
res1
plot(res1, shade.col='deepskyblue', col='deepskyblue')

# Example 2
# H0: mu = 170
# Ha: mu != 170 with sigma2=25
x <- rnorm(n=80, mean=171, sd=5)
res2 <- z.test(x=x, mu=170, sigma2=25, alternative='two.sided')
res2
plot(res2, shade.col='indianred1', col='indianred1')

fhernanb/stests documentation built on March 29, 2025, 10:36 a.m.