hadley/stats337 resource
Readings in applied data science observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
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: 3082
- days_rel: n/a
- days_push: 2995
- n_releases_24m: 0
Adoption not part of the score
1612 stars · 223 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A curated reading list for Stanford's Stats 337 discussion course on applied data science, maintained by Hadley Wickham. It collects papers, blog posts, and weekly course materials covering topics like tidy data, ethics, and collaboration.
Use cases
- find readings for a data science course
- self-study applied data science
- build a university data science curriculum
- find papers on data science ethics and best practices
- learn about tidy data and reproducible research
When to choose
- you want a curated, opinionated reading list on applied data science
- you are teaching or designing a data science discussion course
- you want short papers and blog posts rather than textbooks
When to avoid
- you need executable software or code tools
- you want a systematic, comprehensive survey of data science
- you need up-to-date material, as the course was last updated in 2018
Facets
learning-resource · maturity maintenance
documentation data-science education tutorials cli course-materials readings r stanford curriculum
1 source
- readme: https://github.com/hadley/stats337 · fetched 2026-08-28 · f8e103b389df
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| hadley/stats337 | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem