Bayesian analysis and Statistical Rethinking posts
I haven’t been shy about being a fan of Statistical Rethinking by Dr. Richard McElreath. Reading the book, following lectures, and doing problems, has helped me be more comfortable with statistical concepts that previously went over my head.
One of the things that helped me learn was writing and coding out solutions. These posts may have been problems directly from the book. Other times I went down rabbit holes stemming from my own curiosity. I’m compiling the posts here to help those who may be going through the course or learning PyMC. The order below is intended to be more logical for learning than my blog post page which shows posts in reverse chronological order.
Bayesian statisticsrelated posts before Statistical Rethinking
Posts related to Statistical Rethinking

Prior, prior predictive, likelihood, posterior, and posterior predictive]

Linear regression part 2: understanding the posterior distribution
Of course, there’s still more for me to learn and these posts aren’t perfect. The image shown above is from a post on diagnosing model failure, which was in one of the later lessons of the book. I wanted to highlight it because “failure” is necessary for learning.
I’d welcome feedback at ben.lacar AT gmail.com.