statsmodels.stats.proportion.binom_test¶
- statsmodels.stats.proportion.binom_test(count, nobs, prop=0.5, alternative='two-sided')[source]¶
Perform a test that the probability of success is p.
This is an exact, two-sided test of the null hypothesis that the probability of success in a Bernoulli experiment is p.
- Parameters:
count ({int, array_like}) – the number of successes in nobs trials.
nobs (int) – the number of trials or observations.
prop (float, optional) – The probability of success under the null hypothesis, 0 <= prop <= 1. The default value is prop = 0.5
alternative (str in ['two-sided', 'smaller', 'larger']) – alternative hypothesis, which can be two-sided or either one of the one-sided tests.
- Returns:
p-value – The p-value of the hypothesis test
- Return type:
Notes
This uses scipy.stats.binom_test for the two-sided alternative.
