My assumptions about you

If you’re looking at this project, I’m guessing you’re either a graduate student or a post-graduate academic or researcher of some sort. So I’m presuming you have at least a 101-level foundation in statistics. If you’re rusty, check out Legler and Roback’s free bookdown text, Broadening Your Statistical Horizons. I’m also presuming you’re at least vaguely familiar with Bayesian statistics. If you’re totally new to Bayesian regression and HMC estimation, you might want to look at this paper, watch a few of these engaging lectures, or even start with my other project based on this excellent text. I’m also presuming a basic working fluency in R and a vague idea about what the tidyverse is. If you’re totally new to R, consider starting with Peng’s R Programming for Data Science. And the best introduction to the tidyvese-style of data analysis I’ve found is Grolemund and Wickham’s R for Data Science.

That said, you do not need to be totally fluent in statistics or R. Otherwise why would you need this project, anyway? IMO, the most important things are curiosity, a willingness to try, and persistent tinkering. I love this stuff. Hopefully you will, too.