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:
difffloat

difference in the estimated means or statistics under the alternative.

powerfloat 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.

alphafloat 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_nullfloat

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

std_alternativefloat

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:
nobsfloat

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: Jun 14, 2024