# statsmodels.stats.stattools.jarque_bera¶

statsmodels.stats.stattools.jarque_bera(resids, axis=0)[source]

The Jarque-Bera test of normality.

Parameters
residsarray_like

Data to test for normality. Usually regression model residuals that are mean 0.

axisint, optional

Axis to use if data has more than 1 dimension. Default is 0.

Returns
JB

The Jarque-Bera test statistic.

JBpv

The pvalue of the test statistic.

skew

Estimated skewness of the data.

kurtosis

Estimated kurtosis of the data.

Notes

Each output returned has 1 dimension fewer than data

The Jarque-Bera test statistic tests the null that the data is normally distributed against an alternative that the data follow some other distribution. The test statistic is based on two moments of the data, the skewness, and the kurtosis, and has an asymptotic $$\chi^2_2$$ distribution.

The test statistic is defined

$JB = n(S^2/6+(K-3)^2/24)$

where n is the number of data points, S is the sample skewness, and K is the sample kurtosis of the data.