# gedeck/practical-statistics-for-data-scientists

Code repository for O'Reilly book

Repository: https://github.com/gedeck/practical-statistics-for-data-scientists
Canonical: https://ross.abutalabs.com/products/practical-statistics-for-data-scientists
Language: Jupyter Notebook
License: GPL-3.0
License Family: copyleft
Last push: 2026-08-16T13:15:38+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 100
- inputs: {"age_days": 2389, "days_push": 17, "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 3368, forks 1986 (observed 2026-08-28T04:07:58.340327+00:00)

## What it is
Companion code repository of Jupyter notebooks for the O'Reilly book 'Practical Statistics for Data Scientists', covering 50+ essential statistical concepts using R and Python. Note that the repo is no longer maintained in favor of a new repository for the third edition.

## Use cases
- learn practical statistics for data science
- run book examples in python and r notebooks
- study statistical concepts like regression and classification
- find code for statistical machine learning examples
- supplement a statistics course with hands-on notebooks

## When to choose
- you are reading the book and want runnable code
- you prefer learning statistics through executable notebooks
- you want examples in both R and Python

## When to avoid
- you need actively maintained code or support
- you want the third edition content - use the successor repository
- you need production statistical software rather than educational examples

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, math, developer-tools
- domain: data-science, tutorials, education
- platform: python, jvm, cross-platform
- tags: jupyter-notebooks, statistics, r, oreilly-book, companion-code

## Member repositories
- gedeck/practical-statistics-for-data-scientists (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:58.340327+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 2026-08-29T18:39:58.772312+00:00, confidence not recorded.
  - readme: https://github.com/gedeck/practical-statistics-for-data-scientists (fetched 2026-08-28T04:07:58.340327+00:00, sha aab92eb168b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.