Bayesian statistics offers an intuitive alternative to frequentist methods, yet many instructors hesitate to teach it because it wasn’t part of their own training. This guide provides the conceptual framework necessary to introduce these methods confidently, regardless of your mathematical background.
We have structured this course into five short modules designed to scaffold your understanding. You do not need to become an expert overnight; the goal is to master the core logic—Priors, Posteriors, and Likelihoods—well enough to facilitate student discussion. We focus on conceptual clarity and practical teaching analogies rather than derivation.
If this is new to you—if you're learning Bayesian statistics for the first time through this course, that's completely fine. In fact, it might even be an advantage. Many of the greatest teaching moments come from learning alongside others.
As instructors, we are lifelong learners. It's perfectly okay – and often incredibly empowering for students – to share your own learning journey. You might say something like:
"I wasn't taught Bayesian statistics when I was a student, but I've been learning it because I think it's a better fit for the kinds of questions we ask in biology. Let's explore it together."
Your authenticity will foster an engaging and open learning environment. And science isn't about knowing everything; it's about being curious and updating your understanding when better tools come along.
For students: If your instructor is teaching you Bayesian methods, they're giving you a significant advantage. You're learning tools that many current researchers didn't have access to in their training. And they're committed to making sure you have exposure to new and useful ideas.
Your journey to teaching Bayesian statistics begins here. Click on Module 1 to dive in!
How Bayes is different from other hypothesis tests and an overview of the conceptual basis.
The fundamentals of Bayesian logic; learn key terms to "speak Bayes."
Using Bayes to compare multiple hypotheses at once.
How to conduct a Bayesian statistical test and interpret the results, A step-by-step guide.
How Bayesian ideas shape our understanding in the life sciences and in our daily lives.