Exploration of Joint PMFs: Their Applications in Data Science (Part 1)

Introduction to Joint PMFs

When dealing with discrete random variables, the joint probability mass function (PMF) is a fundamental concept in probability theory and statistics. Understanding it is crucial for analyzing the relationships between different random variables and for performing multivariate probability calculations. For instance, if you have two discrete random variables, X and Y, the joint PMF gives you the probability that Y takes on a specific value x and Y takes on a specific …

data data analysis data science probability probability theory