statsmodels.stats.proportion.proportions_chisquare(count, nobs, value=None)[source]

test for proportions based on chisquare test


count : integer or 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 : integer

the number of trials or observations, with the same length as count.

value : None or float or array_like


chi2stat : float

test statistic for the chisquare test

p-value : float

p-value for the chisquare test

(table, expected) :

table is a (k, 2) contingency table, expected is the corresponding table of counts that are expected under independence with given margins


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.

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