jarque bera test - v2.py

from scipy.stats import jarque_bera
import numpy as np

# generate two sample datasets
data1 = np.random.normal(0, 1, size=100)
data2 = np.random.uniform(size=100)

# perform Jarque-Bera test on each dataset
jb_stat1, jb_p1 = jarque_bera(data1)
jb_stat2, jb_p2 = jarque_bera(data2)

# print the results
print("Jarque-Bera statistic (data1):", jb_stat1)
print("p-value (data1):", jb_p1)
print("Jarque-Bera statistic (data2):", jb_stat2)
print("p-value (data2):", jb_p2)

# perform hypothesis testing
alpha = 0.05
if jb_p1 > alpha:
    print("The null hypothesis (data1 comes from a normal distribution) cannot be rejected.")
else:
    print("The null hypothesis (data1 comes from a normal distribution) is rejected.")
   
if jb_p2 > alpha:
    print("The null hypothesis (data2 comes from a normal distribution) cannot be rejected.")
else:
    print("The null hypothesis (data2 comes from a normal distribution) is rejected.")