Resources
Curated tools, books, courses, and communities to level up your stats game
Everything here is something I’ve personally used, read, or can vouch for. No affiliate links — just resources I genuinely think are worth your time.
Books
📕 The Art of Statistics — David Spiegelhalter
The best “stats for everyone” book. Spiegelhalter uses real stories to explain statistical thinking without equations. Start here if you’re brand new.
📗 Naked Statistics — Charles Wheelan
Funny, accessible, and packed with real-world examples. Great for understanding why statistics matters in everyday life.
📘 An Introduction to Statistical Learning (ISLR) — James, Witten, Hastie, Tibshirani
The bridge between statistics and machine learning. Free PDF available at statlearning.com. The R labs are excellent.
📙 Statistical Rethinking — Richard McElreath
If you want to understand Bayesian statistics properly, this is the gold standard. Challenging but rewarding, with amazing R and Stan code examples.
Free Courses
🎓 Khan Academy — Statistics & Probability
The best free foundation. Clear videos, practice exercises, covers everything from basics to inference.
🎓 StatQuest (YouTube)
Josh Starmer explains statistics and ML with simple visuals and catchy jingles. Surprisingly effective.
🎓 Harvard CS109 — Data Science
Full Harvard course with lectures, labs, and assignments. Bridges stats and practical data science beautifully.
🎓 Seeing Theory
Interactive visualisations of probability and statistics concepts. Built by Brown University. Beautiful and educational.
Tools We Use
🔧 R & Positron
Our language and IDE of choice. R is unmatched for statistical computing, and Positron is a modern, fast editor built for data science.
🔧 Quarto
What this site is built with. Write documents, blogs, and presentations that mix text, code, and output.
🔧 Stan
The gold standard for Bayesian modeling. Steep learning curve, but incredibly powerful for serious statistical work.
🔧 Shiny
Build interactive web apps from R. Great for creating data explorations and teaching tools.
Communities
💬 Cross Validated (Stack Exchange)
The best Q&A site for statistics. Search before you ask — most common questions have excellent answers already.
💬 R-bloggers
Aggregated blog posts from hundreds of R users. Great for discovering tutorials and new packages.
💬 Stan Forums
Incredibly helpful community for Bayesian modelling questions. The developers themselves answer questions.
💬 Posit Community
For R, Shiny, Quarto, and Positron questions. Friendly and welcoming to beginners.
Datasets for Practice
📦 Tidy Tuesday
Weekly datasets released for the R community. Great for practice with real, messy data.
📦 Kaggle Datasets
Thousands of datasets across every domain. Filter by “beginner friendly” to start.
📦 UCI Machine Learning Repository
Classic benchmark datasets used in academic research. The Iris and Wine datasets live here.
📦 Our World in Data
Beautiful, well-documented global datasets on health, economics, education, and more. Perfect for practice with real-world context.
Know something that belongs here? Get in touch — we’re always looking for quality recommendations.