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numpy.random.standard_t() in Python

Last Updated : 18 Aug, 2020
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With the help of numpy.random.standard_t() method, we can get the random samples from standard T distribution having degree of freedom and return the random samples by using this method.

Standard T distribution 

Syntax : numpy.random.standard_t(df, size=None) # Here df is degree of freedom.

Return : Return the random samples as numpy array.

Example #1 :

In this example we can see that by using numpy.random.standard_t() method, we are able to get the random samples of standard T distribution with degree of freedom and return the numpy array.

Python3




# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_t() method
gfg = np.random.standard_t(5, 5000)
  
plt.hist(gfg, bins = 50, density = True)
plt.show()


Output :

Example #2 :

Python3




# import numpy
import numpy as np
import matplotlib.pyplot as plt
  
# Using standard_t() method
gfg = np.random.standard_t(7, 10000)
  
plt.hist(gfg, bins = 50, density = True)
plt.show()


Output :


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