I recently added The Book of R (2nd edition) to my collection—thanks to No Starch Press for the review copy!—and I wanted to share some thoughts for anyone looking to learn R or deepen their statistical programming skills.

My R Journey

My first real exposure to R came while mentoring a Master's student through dissertation research. That's when I discovered the power of ggplot2 for creating beautiful visualizations, Shiny for building interactive web apps, and RMarkdown for reproducible research. It opened my eyes to what R could do beyond basic statistics.

What Makes This Book Different

Author Tilman M. Davies, from the University of Otago's Department of Mathematics and Statistics, originally developed this content for a 3-day R workshop. What transformed it into something special is his teaching approach.

I remember my first-year university textbooks requiring us to work through statistical examples with paper, calculator, and spreadsheets. Davies takes a completely different approach: he presents the equation, the R code, the actual input/output, and then ties it all together with clear explanations. This integration makes statistical concepts genuinely easier to grasp.

A Personal Test

I should note that the last time I coded in R was over 5 years ago. This book brought me back up to speed quickly.

It's comprehensive in the best way, covering both coding concepts and their practical application in statistical analysis. Whether you're starting fresh or returning after a break, the structure works.

Who Should Read This?

If you're buying just one book to get started with R, this is a solid investment. It's designed for complete beginners with no coding experience, covering programming fundamentals within the context of statistical and data analysis. You learn by doing, applying concepts to real problems immediately.

What You Get

Nearly 900 pages across 26 chapters covering:

• The R language

• Programming basics

• Statistics and probability

• Hypothesis testing

• Statistical modeling

• Data visualization

• Plus 2 bonus chapters on development setup, with downloadable exercise solutions and source code included.

Side note: The print quality is exceptional—smooth paper, clear text, no ink bleed-through. Sometimes the little things matter.

Get Your Copy

📖 Direct link to the book: The Book of R, 2nd Edition

💰 Discount code: Use code DATAPROFESSOR when you order on nostarch.com (Valid until January 31, 2026)

Join the Conversation / Giveaway

How are you using R in your work? I'd love to hear about your use cases! Drop a comment in this LinkedIn post for a chance to win a copy of the book, I'll pick from the comments and announce the winner very soon!