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NumPy: Generate an array of 15 random numbers from a standard normal distribution

NumPy: Basic Exercise-18 with Solution

Write a NumPy program to generate an array of 15 random numbers from a standard normal distribution.

Sample Solution :

Python Code :

# Importing the NumPy library with an alias 'np'
import numpy as np

# Generating an array of 15 random numbers from a standard normal distribution using np.random.normal()
rand_num = np.random.normal(0, 1, 15)

# Printing a message indicating 15 random numbers from a standard normal distribution
print("15 random numbers from a standard normal distribution:")

# Printing the array of 15 random numbers
print(rand_num) 

Sample Output:

15 random numbers from a standard normal distribution:
[ 0.42690788  1.81615544  0.36591912 -0.41417837 -1.13061369 -1.31777265
  0.03659045  0.60765805 -0.2148491   0.25934697 -0.89221431  0.33059367
 -0.59079163  0.29665161 -0.2753327 ]                         

Explanation:

The np.random.normal() function generates an array of random numbers from a normal distribution with a mean (loc) of 0 and a standard deviation (scale) of 1. The third argument, 15, specifies the number of random numbers to generate, which is 15 in this case.

Finally print(rand_num) statement prints the generated array of 15 random numbers to the console. The output will vary each time the code is executed due to the random nature of the function.

Python-Numpy Code Editor:

Previous: NumPy program to generate a random number between 0 and 1.
Next: NumPy program to create a vector with values ​​ranging from 15 to 55 and print all values ​​except the first and last.

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