We can generate random numbers from a normal distribution and visualize their distribution with a histogram (see https://www.khanacademy.org/math/probability/statistics-inferential/normal_distribution/v/introduction-to-the-normal-distribution). Draw a normal distribution with the following steps:
Generate random numbers for a given sample size using the
normal()function from therandomNumPy module:N=10000 normal_values = np.random.normal(size=N)
Draw the histogram and theoretical PDF with a center value of
0and standard deviation of1. Use matplotlib for this purpose:_, bins, _ = plt.hist(normal_values, np.sqrt(N), normed=True, lw=1) sigma = 1 mu = 0 plt.plot(bins, 1/(sigma * np.sqrt(2 * np.pi)) * np.exp( - (bins - mu)**2 / (2 * sigma**2) ),lw=2) plt.show()
In the following diagram, we see the familiar bell curve:
