The main reason that we emphasize the cumulative distribution function is because, once we have access to it, we can compute any probabilities associated with the model. This is because the cdf is a universal way to specify a random variable. In particular, there is no distinction between the descriptions for continuous or discrete data. The density function of a random variable is also an important concept so we will present it in the next section. In this section, we will see how to use the cdf to do computations related to a random variable.
The functions that we will use with distributions are part of SciPy and contained in the scipy.stats module, which we import with the following code:
import scipy.stats as st
After this, we can refer to functions in the package with the abbreviation st.
This module contains a large number of predefined distributions, and we encourage you to visit the official documentation at http://docs.scipy.org/doc/scipy/reference...