statsmodels.stats.proportion.proportions_chisquare¶
- statsmodels.stats.proportion.proportions_chisquare(count, nobs, value=None)[source]¶
test for proportions based on chisquare test
- Parameters:
- count{
int
, array_like} the number of successes in nobs trials. If this is array_like, then the assumption is that this represents the number of successes for each independent sample
- nobs
int
the number of trials or observations, with the same length as count.
- value
None
orfloat
or array_like
- count{
- Returns:
Notes
Recent version of scipy.stats have a chisquare test for independence in contingency tables.
This function provides a similar interface to chisquare tests as
prop.test
in R, however without the option for Yates continuity correction.count can be the count for the number of events for a single proportion, or the counts for several independent proportions. If value is given, then all proportions are jointly tested against this value. If value is not given and count and nobs are not scalar, then the null hypothesis is that all samples have the same proportion.