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# statsmodels.jarque_bera() in Python

• Last Updated : 26 Mar, 2020

With the help of `statsmodels.jarque_bera()` method, we can get the jarque bera test for normality and it’s a test based on skewness, and the kurtosis, and has an asymptotic distribution.

Syntax : `statsmodels.jarque_bera(residual, axis)`
Return : Return the jarque bera test statistics, pvalue, skewness, and the kurtosis.

Example #1 :
In this example we can see that by using `statsmodels.jarque_bera()` method, we are able to get the jarque bera test statistics, pvalue, skewness and kurtosis by using this method.

 `# import numpy and statsmodels``import` `numpy as np``from` `statsmodels.stats.stattools ``import` `jarque_bera`` ` `g ``=` `np.array([``1``, ``2``, ``3``])``# Using statsmodels.jarque_bera() method``gfg ``=` `jarque_bera(g)`` ` `print``(gfg)`

Output :

(0.28125, 0.8688150562628432, 0.0, 1.5)

Example #2 :

 `# import numpy and statsmodels``import` `numpy as np``from` `statsmodels.stats.stattools ``import` `jarque_bera`` ` `g ``=` `np.array([``1``, ``2``, ``3``, ``-``1``, ``-``2``, ``-``3``])``# Using statsmodels.jarque_bera() method``gfg ``=` `jarque_bera(g)`` ` `print``(gfg)`

Output :

(0.5625000000000003, 0.7548396019890072, 0.0, 1.4999999999999996)

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