Hi Jannis Liedtke

"Statistical Rethinking" by Richard McElreath and "Doing Bayesian Analysis" by John K. Kruschke are really great entry points. Any book by Andrew Gelman is a reference but maybe better for more advanced readers in my opinion. Hope this helps!

https://xcelab.net/rm/statistical-rethinking/

https://sites.google.com/site/doingbayesiandataanalysis/

https://statmodeling.stat.columbia.edu/books/

Note: Statistical Rethinking also has been 'translated' into brms code by Solomon Kurtz here: https://bookdown.org/content/4857/

brms is a very user-friendly package for Bayesian stats that runs rstan on the background but with simpler syntax

Thanks a lot Raphaël! I will have a look in these books

Dear Jannis,

A student’s guide to Bayesian statistics authored by Lambert is very good.

Hopefully, that can be a help.

Best,

Farahani

Dear Farahani,

that book looks promising, too.

Thanks for the suggestion.

Best

Jannis

You are most welcome

I second the recommendation to read through "Statistical rethinking" as translated by Solomon Kurtz (https://bookdown.org/content/4857/). It's free and presents what is, in my opînion, the most user friendly R package to conduct Bayesian regressions (i.e., brms).

Hi Benjamin, thanks for the link. This ebook might come in handy. looking forward diving into it.

Marc Kery's book's are the best ones in my opinion:

https://www.amazon.com/Introduction-WinBUGS-Ecologists-Bayesian-regression/dp/0123786053

https://www.amazon.com/Bayesian-Population-Analysis-using-WinBUGS/dp/0123870208/ref=pd_lpo_1?pd_rd_i=0123870208&psc=1

P. M. Lee's "Bayesian Statistics: An Introduction" will be helpful to transform classical statistical concepts into a Bayesian framework. It contains many more examples and exercises fr the learners.

"Statistical Rethinking" by Richard McElreath, "Bayesian Statistical Methods" by Brian J. Reich and Sujit K. Ghosh, and "Doing Bayesian Analysis" by John K. Kruschke are the best Introduction books I have found.