AllenDowney/ThinkBayes resource
Code repository for Think Bayes. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4804
- days_rel: n/a
- days_push: 2001
- n_releases_24m: 0
Adoption not part of the score
1702 stars · 1902 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
The companion code repository for 'Think Bayes: Bayesian Statistics Made Simple' by Allen B. Downey, a book published by O'Reilly Media. It contains Python examples and exercises that teach Bayesian statistics through hands-on computation.
Use cases
- learn bayesian statistics with python
- find worked examples of bayes theorem in code
- supplement reading the Think Bayes book
- teach an intro bayesian statistics course
- practice probability modeling with python
When to choose
- you are reading or teaching from the Think Bayes book
- you want code-first, computational introductions to Bayesian methods
- you prefer learning statistics through runnable Python examples
When to avoid
- you need a production Bayesian inference library like PyMC or Stan
- you want actively maintained statistical software
- you need a license-clear codebase for redistribution
Facets
learning-resource · maturity maintenance
data-science math education data-science python bayesian-statistics book textbook probability statistics
1 source
- readme: https://github.com/AllenDowney/ThinkBayes · fetched 2026-08-28 · ed2709b41050
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| AllenDowney/ThinkBayes | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="AllenDowney/ThinkBayes")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem