To reflect the 2021 syllabus changes, the lessons below are being added / changed. The current plan is to have all of these changes done by the end of March, I’m sorry that that isn’t farther from the exam date.
A.3.5 has been removed (Normal-Normal conjugate priors are no longer on the syllabus).
I’ve added a new lesson B.1.0 introducing LMM with an intercept only example. This isn’t related to syllabus changes; the goal is to help clarify why we use random effects as that is something a lot of people ask about.
C.2.5: Multicollinearity is no longer on the reading list and this lesson will be shortened. Target date 3/19
C.2.9 and C.2.10: Probably 2 new lessons will be added to include material on splines, cross-validation, and prior distribution simulations. Target date 3/26
C.3.2: The 2nd edition of Statistical Rethinking adds an example related to shortcomings of Metropolis-Hastings and Gibbs Sampling. Three slides of the lesson (including the exercise) will be updated to reflect this. Target date: 3/13
C.3.5: New lesson on trace rank plots. This is the first fully new lesson to be added as I expect at least one question related to this to appear on the exam this sitting. Target date: 3/13
C.4.1: Edits to reduce the emphasis on general link functions as it seems that only log link (for Poisson) and logit link functions (for binomial) are still on syllabus. Target date: 3/19
C.5.5: New lesson on using uncentered priors to get better convergence of chains. Target date: 3/31.