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
strin[‘two-sided’, ‘smaller’, ‘larger’] alternative hypothesis, which can be two-sided or either one of the one-sided tests.
- count{
- Returns:
- p-value
float The p-value of the hypothesis test
- p-value
Notes
This uses scipy.stats.binom_test for the two-sided alternative.