Stats 3: Advanced & Elective Topics
Everything statistical that neither Statistics 1 nor Statistics 2 has room for. Stats 3 is the elective shelf: seventeen lessons you can take in almost any order, picked up when a thesis, a supervisor or a reviewer asks for one.
Some of it is the natural next step after Stats 2: effect sizes and power done properly, mediation, MANOVA, factor analysis. Some of it is a different way of thinking altogether, like the bootstrap, Bayesian inference, multilevel models and causal diagrams. The rest is here because a particular field needs it: survival analysis, meta-analysis, and the psychophysics pair at the end.
There is no single path through this course. Read the lesson your project needs, follow the links it gives you, and come back when the next question arrives. The ML & AI course reuses several of these models for prediction rather than explanation.