# h-Klok/StatsWithJuliaBook

Repository: https://github.com/h-Klok/StatsWithJuliaBook
Canonical: https://ross.abutalabs.com/products/statswithjuliabook
Homepage: https://statisticswithjulia.org/
Language: Julia
License: MIT
License Family: permissive
Topics: julia-language, julia, statistics, machine-learning
Last push: 2023-03-27T02:18:41+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": 3150, "days_push": 1256, "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 1090, forks 273 (observed 2026-08-28T04:03:32.857187+00:00)

## What it is
A companion repository of 200+ Julia code blocks for the book 'Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence'. It covers probability, statistical inference, regression, machine learning basics, and dynamic model simulation through runnable examples.

## Use cases
- learn statistics with julia
- julia code examples for probability distributions
- hypothesis testing examples in julia
- linear regression tutorial julia
- machine learning basics with julia
- simulate dynamic models in julia
- learn julia for data science

## When to choose
- you want to learn or refresh statistics using Julia
- you know statistics and want to see it implemented in Julia
- you want runnable code accompanying a structured textbook

## When to avoid
- you need a production statistics or ML library rather than educational examples
- you don't use Julia and won't install it
- you need comprehensive machine learning coverage beyond the basics

## Facets
- artifact type: learning-resource
- maturity: stable
- function: data-science, machine-learning, math
- domain: data-science, machine-learning, tutorials, education
- platform: cross-platform
- tags: statistics, julia-language, textbook-code, probability, hypothesis-testing, regression, simulation, julia

## Member repositories
- h-Klok/StatsWithJuliaBook (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:32.857187+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 2026-08-30T06:49:12.964601+00:00, confidence not recorded.
  - readme: https://github.com/h-Klok/StatsWithJuliaBook (fetched 2026-08-28T04:03:32.857187+00:00, sha 47c7186676ac)
  - homepage: https://statisticswithjulia.org/ (fetched 2026-08-29T12:51:23.450169+00:00, sha 1039d8ebc58b)
- Data as of 2026-08-30T08:39:29.467469+00:00.