This function performs the mean test using summarized data (values).
z_test(
meanx,
nx,
sigma2 = NULL,
alternative = "two.sided",
mu = 0,
conf.level = 0.95
)Arguments
- meanx
sample mean for sample x.
- nx
sample size for sample x.
- sigma2
population variance which is known.
- alternative
a character string specifying the alternative hypothesis, must be one of
two.sided(default),greaterorless. 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 13.1 from Freund et al. (2000)
res1 <- z_test(meanx=8.091, nx=25, mu=8, sigma2=0.16^2, alternative='two.sided')
res1
#>
#> Z test for mean
#>
#> data: x
#> Z = 2.8437, p-value = 0.004459
#> alternative hypothesis: true is not equal to 8
#> 95 percent confidence interval:
#> 8.028281 8.153719
#> sample estimates:
#> mean of x
#> 8.091
#>
plot(res1)
# Example 13.2 from Freund et al. (2000)
res2 <- z_test(meanx=21819, nx=100, mu=22000, sigma2=1295^2, alternative='less')
res2
#>
#> Z test for mean
#>
#> data: x
#> Z = -1.3977, p-value = 0.0811
#> alternative hypothesis: true is less than 22000
#> 95 percent confidence interval:
#> -Inf 22032.01
#> sample estimates:
#> mean of x
#> 21819
#>
plot(res2)
