Description Usage Arguments Details Value Examples
View source: R/pwr_t_test_1pop.R
pwr_t_test_1pop
computes the power and the sample size for testing
mean in a normal variable with unknown variance.
1 2 | pwr_t_test_1pop(m, m0, sigma, n = NULL, pwr = NULL,
alternative = "two.sided", sig_level = 0.05)
|
m |
populational mean |
m0 |
mean under null hypothesis |
sigma |
populational standard deviation |
n |
number of observations (sample size) |
pwr |
power of test 1 + β (1 minus type II error probability) |
alternative |
a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less" |
sig_level |
significance level (Type I error probability) |
Exactly one of the parameters 'n' and 'pwr' must be passed as NULL, and that parameter is determined from the other. Notice that the last one has non-NULL default so NULL must be explicitly passed if you want to compute it.
This function computes internally the effect size, given the population mean, mean under null hypothesis and the population standard deviation. These three parameters are required.
pwr_t_test_1pop
returns a list with the following components:
populational mean
mean under null hypothesis
populational standard deviation.
significance level
A tibble
with sample size n
and
power pwr
1 2 3 4 5 6 | # Power
pwr_t_test_1pop(m = 20, m0 = 10, sigma = 10, n = 25, pwr = NULL,
alternative = "two.sided", sig_level = 0.05)
# Sample size
pwr_t_test_1pop(m = 20, m0 = 10, sigma = 10, n = NULL, pwr = 0.95,
alternative = "two.sided", sig_level = 0.05)
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