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.
z.test(x, mu = 0, stdev, alternative = c("two.sided", "less", "greater"), sd = stdev, conf.level = 0.95, ...)
- Vector of data values.
- Hypothesized mean of the population.
- Known standard deviation of the population.
- Direction of the alternative hypothesis.
- Alternative to
- Confidence level for the interval computation.
- Additional arguments are silently ignored.
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
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
- An object of class
htestcontaining the results
This function should be used for learning only, real data should
x <- rnorm(25, 100, 5) z.test(x, 99, 5)