Portuguese (Brazilian) users

This is a call to action to Portuguese-speaking users (specially Brazilians). I am currently teaching Bayesian stats to graduate students at Universidade Nove de Julho - UNINOVE, located in São Paulo, Brazil.

I’ve found a hard time finding Portuguese material on bayesian stats (forget about Portuguese materials on Stan). So before the fall semester last year (2020) I’ve managed to put a short series of tutorials on Bayesian stats and Stan (mostly using rstanarm and a little bit of brms). These material are available at GitHub on storopoli/Estatistica-Bayesiana and also as a distill website in storopoli.io/Estatistica-Bayesiana. They are all under CC BY-SA license.

If anybody wants to join any help is mostly appreciated and welcome. I am currently working in the 2021-02 branch for the next fall semester. I am using quite an inclusive language and approach, making use of graphical intuition whenever possible, since this is most likely the first contact that students will be having on Bayesian stats. Attribution (authorship) is offered to everybody that makes contributions.



You are right there’s a relative scarcity of quality material about Bayesian statistics in Portuguese.
For future reference, here are few resources:

  • @randommm 's Apostila de Stan is a valuable resource in Portuguese for those who want to learn Stan in particular.
  • Rafael Stern, Luis Esteves and Rafael Izbicki (UFSCar) have put these notes together which address Bayesian stats at an intermediate level.
  • Ricardo Ehlers (USP) has these notes, which, whilst more mathematical than the material you have started to compile, are also introductory in nature.

None of these “compete” with the material you have put together, which is more introductory.

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@maxbiostat thank you!

I did knew Stern et al. notes. But they emphasize heavily on math and I wanna a more intuitive graphical approach (mostly uninitiated social science PhD candidates).

Regarding the other two, for me they are novel. Thank you.

I will use these notes when possible and also cite them on the front matter (index.html and README.md) of the content.

Thank you!

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