z.test: Z test for known population standard deviation
In TeachingDemos: Demonstrations for Teaching and Learning

z.test

R Documentation

Z test for known population standard deviation

Description

Compute the test of hypothesis and compute confidence interval on the mean of a population when the standard deviation of the population is known.

Usage

z.test(x, mu = 0, stdev, alternative = c("two.sided", "less", "greater"),
  sd = stdev, n=length(x), conf.level = 0.95, ...)

Arguments

`x`	Vector of data values or the mean of the data.
`mu`	Hypothesized mean of the population.
`stdev`	Known standard deviation of the population.
`alternative`	Direction of the alternative hypothesis.
`sd`	Alternative to `stdev`
`n`	The sample size if `x` is the sample mean.
`conf.level`	Confidence level for the interval computation.
`...`	Additional arguments are silently ignored.

Details

Many introductory statistical texts introduce inference by using the Z test and Z based confidence intervals based on knowing the population standard deviation. Most statistical packages do not include functions to do Z tests since the T test is usually more appropriate for real world situations. This function is meant to be used during that short period of learning when the student is learning about inference using Z procedures, but has not learned the T based procedures yet. Once the student has learned about the T distribution the t.test function should be used instead of this one (but the syntax is very similar, so this function should be an appropriate introductory step to learning t.test).