# 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 (integer or array_like) – the number of successes in nobs trials. nobs (integer) – 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 (string in ['two-sided', 'smaller', 'larger']) – alternative hypothesis, which can be two-sided or either one of the one-sided tests. p-value – The p-value of the hypothesis test float

Notes

This uses scipy.stats.binom_test for the two-sided alternative.