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

Calculates the Jarque-Bera test for normality


Data to test for normality

axisint, optional

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

JBfloat or array

The Jarque-Bera test statistic

JBpvfloat or array

The pvalue of the test statistic

skewfloat or array

Estimated skewness of the data

kurtosisfloat or array

Estimated kurtosis of the data


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.