statsmodels.stats.power.normal_sample_size_one_tail¶

statsmodels.stats.power.normal_sample_size_one_tail(diff, power, alpha, std_null=`1.0`, std_alternative=`None`)[source]

explicit sample size computation if only one tail is relevant

The sample size is based on the power in one tail assuming that the alternative is in the tail where the test has power that increases with sample size. Use alpha/2 to compute the one tail approximation to the two-sided test, i.e. consider only one tail of two-sided test.

Parameters:
diff`float`

difference in the estimated means or statistics under the alternative.

power`float` `in` `interval` (0,1)

power of the test, e.g. 0.8, is one minus the probability of a type II error. Power is the probability that the test correctly rejects the Null Hypothesis if the Alternative Hypothesis is true.

alpha`float` `in` `interval` (0,1)

significance level, e.g. 0.05, is the probability of a type I error, that is wrong rejections if the Null Hypothesis is true. Note: alpha is used for one tail. Use alpha/2 for two-sided alternative.

std_null`float`

standard deviation under the Null hypothesis without division by sqrt(nobs)

std_alternative`float`

standard deviation under the Alternative hypothesis without division by sqrt(nobs). Defaults to None. If None, `std_alternative` is set to the value of `std_null`.

Returns:
nobs`float`

Sample size to achieve (at least) the desired power. If the minimum power is satisfied for all positive sample sizes, then `nobs` will be zero. This will be the case when power <= alpha if std_alternative is equal to std_null.

Last update: Dec 14, 2023