# z.test

##### Z test for known population standard deviation

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

- Keywords
- htest

##### Usage

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

##### Arguments

- x
- Vector of data values.
- mu
- Hypothesized mean of the population.
- stdev
- Known standard deviation of the population.
- alternative
- Direction of the alternative hypothesis.
- sd
- Alternative to
`stdev`

- conf.level
- Confidence level for the interval computation.
- ...
- Additional arguments are silently ignored.

##### Details

Most 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`

).

##### Value

- An object of class
`htest`

containing the results

##### Note

This function should be used for learning only, real data should
generally use `t.test`

.

##### See Also

##### Examples

```
x <- rnorm(25, 100, 5)
z.test(x, 99, 5)
```

*Documentation reproduced from package TeachingDemos, version 1.0, License: Artistic*