# rmcelreath/stat_rethinking_2023

Statistical Rethinking Course for Jan-Mar 2023

Repository: https://github.com/rmcelreath/stat_rethinking_2023
Canonical: https://ross.abutalabs.com/products/stat_rethinking_2023
Language: R
License: CC0-1.0
License Family: permissive
Last push: 2023-11-28T12:15:06+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 98
- inputs: {"age_days": 1372, "days_push": 1009, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2383, forks 268 (observed 2026-08-28T04:06:42.418551+00:00)

## What it is
Repository of course materials for Richard McElreath's 2023 Statistical Rethinking course, including lecture videos, slides, and problem sets on Bayesian data analysis. It teaches scientific modeling and Bayesian inference for biologists and social scientists.

## Use cases
- learn bayesian data analysis from scratch
- find lecture videos for statistical rethinking course
- get problem sets and solutions for bayesian statistics
- study causal inference and scientific modeling
- self-study the statistical rethinking book
- learn R for bayesian modeling

## When to choose
- you want a free, complete university-level course on Bayesian statistics
- you prefer video lectures paired with a textbook and exercises
- you are a biologist or social scientist learning data analysis

## When to avoid
- you need actively maintained software or a code library
- you want the newest edition (see the 2024 version of the course)
- you need interactive registration or instructor support (registration closed)

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, machine-learning
- domain: data-science, education, tutorials
- platform: python, cross-platform
- tags: bayesian-statistics, course-materials, r, statistical-rethinking, lectures

## Member repositories
- rmcelreath/stat_rethinking_2023 (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:42.418551+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:34:42.175046+00:00, confidence not recorded.
  - readme: https://github.com/rmcelreath/stat_rethinking_2023 (fetched 2026-08-28T04:06:42.418551+00:00, sha 03738fa8ce91)
- Data as of 2026-08-30T08:39:29.467469+00:00.