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https://github.com/robitalec/statistical-rethinking-colearning-2022

Statistical Rethinking colearning 2022
https://github.com/robitalec/statistical-rethinking-colearning-2022

bayesian r rethinking rstats stan statistics

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Statistical Rethinking colearning 2022

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README 

        
---

title: Statistical Rethinking colearning 2022

output: 

  github_document: 

    toc: true

---



```{r include = FALSE}

knitr::opts_chunk$set( fig.path = "graphics/" )

```



---



This repository contains resources and information for a colearning group

meeting regularly to discuss lectures and homework assignments from the 

[Statistical Rethinking 2022](https://github.com/rmcelreath/stat_rethinking_2022)

course. 



## Schedule



Adjusting from Richard's schedule for our pace. Note these are meeting dates

indicating when lectures, readings and homework are **assigned**, to be 

discussed on/completed by the next meeting. 



| Meeting date | Lectures | Reading | Homework |

|---|---|---|---|

| 2022-01-13 | [(1) The Golem of Prague](https://youtu.be/cclUd_HoRlo), [(2) Bayesian Inference](https://www.youtube.com/watch?v=guTdrfycW2Q&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=2) | Chapters 1, 2 and 3 | [Homework 1](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week01.pdf) |

| 2022-01-26 | [(3) Basic Regression](https://www.youtube.com/watch?v=zYYBtxHWE0A), [(4) Categories & Curves](https://youtu.be/QiHKdvAbYII) | Chapter 4 | [Homework 2](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week02.pdf) |

| 2022-02-11 | [(5) Confounding](https://youtu.be/UpP-_mBvECI), [(6) Even Worse Confounding](https://www.youtube.com/watch?v=NSuTaeW6Orc) | Chapters 5 and 6 | [Homework 3](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week03.pdf)  |

| 2022-02-24   |  [(7) Overfitting](https://www.youtube.com/watch?v=odGAAJDlgp8&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=7)| Chapter 7 | | 

| 2022-03-11 | [(8) Markov Chain Monte Carlo](https://www.youtube.com/watch?v=Qqz5AJjyugM&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=8&pp=sAQB) | Chapter 8, 9  |  [Homework 4](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week04.pdf) | 

| 2022-03-25 | [(9) Logistic and Binomial GLMs](https://www.youtube.com/watch?v=nPi5yGbfxuo&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=9), [(10) Sensitivity and Poisson GLMs](https://www.youtube.com/watch?v=YrwL6t0kW2I) | Chapters 10, 11 | [Homework 5](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week05.pdf)  |

| 2022-04-06 | [(11) Ordered Categories](https://www.youtube.com/watch?v=-397DMPooR8&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=11), [(12) Multilevel Models](https://www.youtube.com/watch?v=SocRgsf202M&list=PLDcUM9US4XdMROZ57-OIRtIK0aOynbgZN&index=12) | Chapters 12, 13 | [Homework 6](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week06.pdf)  |

| 2022-04-22 | [(13) Multi-Multilevel Models](https://youtu.be/n2aJYtuGu54), [(14) Correlated varying effects](https://youtu.be/XDoAglqd7ss) | Chapters 13, 14 | [Homework 7](https://github.com/rmcelreath/stat_rethinking_2022/blob/main/homework/week07.pdf)  |



## Resources



* Lectures: https://github.com/rmcelreath/stat_rethinking_2022#calendar--topical-outline

* Homework: https://github.com/rmcelreath/stat_rethinking_2022/tree/main/homework



Additional material using other packages or languages



* Original R: https://github.com/rmcelreath/rethinking/

* R + Tidyverse + ggplot2 + brms: https://bookdown.org/content/4857/

* Python and PyMC3: Python/PyMC3

* Julia and Turing: https://github.com/StatisticalRethinkingJulia and https://github.com/StatisticalRethinkingJulia/TuringModels.jl



See Richard's comments about these here: https://github.com/rmcelreath/stat_rethinking_2022#original-r-flavor



Also, Alec's notes and solutions of the 2019 material: https://github.com/robitalec/statistical-rethinking and https://www.statistical-rethinking.robitalec.ca/



## Installation



Package specific install directions. We'll update these as we go!



Rethinking



* [`rethinking`](https://github.com/rmcelreath/rethinking#installation)



Stan



* [`cmdstanr`](https://mc-stan.org/cmdstanr/articles/cmdstanr.html)

* [`RStan`](https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started)

* [`brms`](r/brms/#how-do-i-install-brms)



Targets



* [`targets`](https://github.com/ropensci/targets/#installation)

* [`stantargets`](https://github.com/ropensci/stantargets/#installation)



V8, needed for the `dagitty` package



* [`V8`](https://github.com/jeroen/v8#installation)



## Project structure



This repository is structured with a `homework/` folder for homework solutions, 

and `notes/` folder for notes. For folks joining in the colearning group, 

you are encouraged to make your own branch in this repository and

share your notes and/or homework solutions. 



The `R/` folder can be used to store reusable functions useful across

homework solutions and your own model situations. 



For example, the `dag_plot` function makes a DAG plot from a DAG: 



```{r readme_dag, cache = TRUE}

library(ggplot2)

library(ggdag)

library(dagitty)



source('R/dag_plot.R')



dag <- dagify(

    Z ~ A + B,

    B ~ A,

    exposure = 'A',

    outcome = 'Z'

)



dag_plot(dag)

```



## Branches



See the full list of [branches](https://github.com/robitalec/statistical-rethinking-colearning-2022/branches). 



* [Matteo](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/matteo)

* [Jillian](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/jillian)

* [Alec](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/alec)

* [Levi](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/levi)

* [Katrien](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/katrien)

* [Bella](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/bella)

* [Hannah](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/hannah)

* [Frankie](https://github.com/robitalec/statistical-rethinking-colearning-2022/tree/frankie)



## Thanks



Many thanks to Richard McElreath for a continued emphasis on teaching 

Bayesian statistics and for providing this incredible resource of lectures

and homework assignments free for everyone. 



Also thank you to the developers of R, Stan and innumerous R packages that 

allow us to pursue this interest. 



## Code of Conduct



Please note that this project is released with a [Code of

Conduct](CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.