- dask.array.stats.chisquare(f_obs, f_exp=None, ddof=0, axis=0)¶
Calculate a one-way chi-square test.
Please see the docstring for
scipy.stats.chisquare()for complete information including notes, references, and examples.
Some inconsistencies with the Dask version may exist.
The chi-square test tests the null hypothesis that the categorical data has the given frequencies.
Observed frequencies in each category.
- f_exparray_like, optional
Expected frequencies in each category. By default the categories are assumed to be equally likely.
- ddofint, optional
“Delta degrees of freedom”: adjustment to the degrees of freedom for the p-value. The p-value is computed using a chi-squared distribution with
k - 1 - ddofdegrees of freedom, where k is the number of observed frequencies. The default value of ddof is 0.
- axisint or None, optional
The axis of the broadcast result of f_obs and f_exp along which to apply the test. If axis is None, all values in f_obs are treated as a single data set. Default is 0.
- res: Delayed Power_divergenceResult
An object containing attributes:
- chisqfloat or ndarray
The chi-squared test statistic. The value is a float if axis is None or f_obs and f_exp are 1-D.
- pvaluefloat or ndarray
The p-value of the test. The value is a float if ddof and the return value chisq are scalars.