用Python学分析-正态分布

 1 import numpy as np
 2 import scipy.stats as stats
 3 import matplotlib.pyplot as plt
 4 
 5 mu = 0 # mean
 6 sigma = 1 # standart deviation
 7 x = np.arange(-5, 5, 0.1)
 8 y = stats.norm.pdf(x, 0, 1)
 9 print('Chart 1:')
10 plt.plot(x, y)
11 plt.title('Normal: $\mu$ = {0:.1f}, $\sigma^2$ = {1:0.1f}'.format(mu, sigma))
12 plt.xlabel('x')
13 plt.ylabel('Probability density') # probobility of observing each of these observations
14 plt.show()

 1 import numpy as np
 2 from scipy.stats import norm
 3 
 4 n = 100
 5 x = np.arange(0, 0.1, 0.01)
 6 y = np.arange(0, 3.1, 0.1)
 7 print('z表       ', end = '')
 8 for j in x:
 9     print( str(j), end='    ')
10 print()
11 for i in y:
12     print( i , end = ':   ')
13     for j in x:
14         z = norm.cdf(j+i)
15         print('{0:.4f}'.format(z), end = '  ')
16     print('')