# andrewgbruce/statistics-for-data-scientists

Code and data associated with the book "Statistics for Data Scientists: 50 Essential Concepts"

Repository: https://github.com/andrewgbruce/statistics-for-data-scientists
Canonical: https://ross.abutalabs.com/products/statistics-for-data-scientists
Language: R
License Family: other
Last push: 2022-12-16T01:16:27+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3412, "days_push": 1357, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1231, forks 663 (observed 2026-08-28T04:04:04.219601+00:00)

## What it is
Companion code and data repository for the book 'Practical Statistics for Data Scientists: 50 Essential Concepts', containing R scripts organized by chapter that replicate the book's figures and examples. It serves as a hands-on learning resource for applying statistical concepts in data science.

## Use cases
- learn statistics for data science with practical R code
- replicate book figures and examples in R
- study essential statistical concepts like sampling, regression, and classification
- download and explore datasets used in a statistics textbook
- supplement self-study of practical statistics

## When to choose
- you are reading the book and want runnable code for its examples
- you want to learn applied statistics through R scripts
- you need example datasets for practicing statistical analysis

## When to avoid
- you need a production statistics library rather than educational scripts
- you work in Python and want the original book's code (the maintained repo is gedeck/practical-statistics-for-data-scientists)
- you expect a maintained software package with releases and support

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: data-science, analytics
- domain: data-science, tutorials
- platform: python, cross-platform
- tags: r, statistics, book-companion, educational

## Member repositories
- andrewgbruce/statistics-for-data-scientists (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:04.219601+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 2026-08-30T08:22:24.980792+00:00, confidence not recorded.
  - readme: https://github.com/andrewgbruce/statistics-for-data-scientists (fetched 2026-08-28T04:04:04.219601+00:00, sha 7e80d80f5f01)
- Data as of 2026-08-30T08:39:29.467469+00:00.