Working with Randomness and Probability

In this chapter, we will discuss randomness and probability. We will start by briefly exploring the fundamentals of probability by selecting elements from a set of data. Then, we will learn how to generate (pseudo) random numbers using Python and NumPy, and how to generate samples according to a specific probability distribution. We will conclude the chapter by looking at a number of advanced topics covering random processes and Bayesian techniques and using Markov Chain Monte Carlo (MCMC) methods to estimate the parameters of a simple model.

Probability is a quantification of the likelihood of a specific event occurring. We use probabilities intuitively all of the time, although sometimes the formal ...

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