Welcome to the final module. Over the last four lessons, we’ve motivated, defined, and applied Bayesian statistics. You’ve moved from the “why” (Module 1), to the “what” (Module 2), to the “how” (Modules 3 & 4).
In this capstone module, we’ll explore the “so what?” We’ll see that Bayesian logic isn’t just a new way to run a t-test. It’s a powerful framework that scientists are using to model life itself. From how our brains interpret the world to how animals forage for food, the principles of Bayesian inference—priors, likelihoods, and updating—are everywhere. This module will connect the stats you just learned to the core concepts you already teach in biology, psychology, and neuroscience.