stat_rethinking_2020
Statistical Rethinking Course Winter 2020/2021 (by rmcelreath)
stat_rethinking_2022
Statistical Rethinking course winter 2022 (by rmcelreath)
stat_rethinking_2020  stat_rethinking_2022  

8  13  
651  4,107  
    
2.6  1.8  
over 3 years ago  over 2 years ago  
R  R  
   
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars  the number of stars that a project has on GitHub. Growth  month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars  the number of stars that a project has on GitHub. Growth  month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stat_rethinking_2020
Posts with mentions or reviews of stat_rethinking_2020.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 20220507.

[Q] Book on Bayesian statistics?
Bayesian rethinking is quite a good book and has been translated to Python.
 [E] Statistical Rethinking 2022 by Richard McElreath

I have a small sample size time series with potentially lagged predictor values which are also time series. What could be potential methods to analyse these data?
If you want a full course on Bayesian Multilevel models, there's the excellent "statistical rethinking": lectures/content here and code here

How to incorporate Bayes Inference into inplay betting model using R?
If you're unfamiliar with Bayesian analysis, I recommend reading Richard McElreath's Statistical Rethinking. It has associated R exercises and a lectures (found here)
 Any good video series for learning Bayesian stats?

Quantitative Methods Course
A wonderful introductory course from a Bayesian point of view: https://github.com/rmcelreath/stat_rethinking_2020

Any resource suggestion for 6420 Bayesian Statistics?
https://github.com/rmcelreath/stat_rethinking_2020 includes slides and videos.
stat_rethinking_2022
Posts with mentions or reviews of stat_rethinking_2022.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 20230105.

Is there another way to determine the effect of the features other than the inbuilt features importance and SHAP values? [Research] [Discussion]
I would recommend the lectures and book of Statistics Rethinking: https://github.com/rmcelreath/stat_rethinking_2022

[Q] How is multilevel modelling different from a simple interaction/ moderation term?
Not a direct answer to your question, but I'd highly recommend Richard McElreath's lectures and book for learning multilevel modelling.

Resources for learning Bayesian stats
Statistical Rethinking is an awesome Bayesian introductory course for people that already know some statistical modeling (i.e. GLM, HLM, ...) from the frequentist side.
 Boss wants me to model a process and tweak the parameters to minimize the response variable. How can I do that? e.g. number of customers waiting in a bank.
 Short Course on Statistics for Lab Scientists?
 Minimální znalost statistiky pro junior Data Scientist / Engineer pozici (ve finančnim sektoru)?
 Need a data set that I can do linear regression on but also apply hierarchical modelling via Bayesian methods.
 Statistical Rethinking (2022 Edition)

How to be a biz/tech Anthropologist
Either way, try to pick up some computational and especially statistical expertise on the side. If you can't find coursework for it at your uni, I highly recommend McElreath's Statistical Rethinking. He recently started his lecture series for this year, with resources openly available: https://github.com/rmcelreath/stat_rethinking_2022
What are some alternatives?
When comparing stat_rethinking_2020 and stat_rethinking_2022 you can also consider the following projects:
brms  brms R package for Bayesian generalized multivariate nonlinear multilevel models using Stan
botorch  Bayesian optimization in PyTorch
stan  Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
interpretablemlbook  Book about interpretable machine learning
stat_rethinking_2023  Statistical Rethinking Course for JanMar 2023
pymcresources  PyMC educational resources