Time for action – drawing a normal distribution

Random numbers can be generated from a normal distribution and their distribution may be visualized with a histogram. To draw a normal distribution, perform the following steps:

1. Generate random numbers for a given sample size using the normal function from the random NumPy module.

   N=10000
   normal_values = np.random.normal(size=N)

2. Draw the histogram and theoretical pdf: Draw the histogram and theoretical pdf with a center value of 0 and standard deviation of 1. We will use Matplotlib for this purpose.

   dummy, bins, dummy = 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 screenshot, we see the familiar bell curve:

   

What just happened?

We visualized the normal distribution using the normal function from the random NumPy module. We did this by drawing the bell curve and a histogram of randomly generated values...