BiteSize Statistics for Absolute Beginners: Key Probability Distributions is the third and final course in the BiteSize Stats for Absolute Beginners specialization. It shows how the probability rules from Course 2 turn into named, reusable models — random variables and their distributions, the binomial and Poisson families for discrete counts, the Normal distribution for continuous measurements, and the sampling distributions that connect any of them back to real data.
Across five modules, learners progress from random variables, PMFs, expected value, and CDFs, through the binomial distribution for fixed-trial counts and the Poisson distribution for rate-based counts, to the Normal distribution, Z-scores, and inverse-Normal problems, and finally the Central Limit Theorem and sampling distributions of the mean and proportion. Every core lesson pairs a short video walkthrough and reading with a hands-on interactive notebook built around a realistic business scenario, and each module closes with a graded applied lab using a real dataset; two modules also include a fully worked bonus case study.
