Statistical Computing in the Age of AI

A graduate textbook in biostatistics

Author

The rgtlab Curriculum Project

Published

2026-04-29

Welcome

This is the online version of Statistical Computing in the Age of AI by The rgtlab Curriculum Project, a graduate textbook in statistical computing for biostatistics students.

The book is a practical, code-first introduction to the computing techniques that biostatisticians use daily: programming in R, version control, linear algebra, simulation, statistical modelling, graphics, reproducible software, and the emerging role of large language models in each of these activities.

It is written in the tradition of the Posit book family (R for Data Science, Advanced R, R Packages) and uses the same Quarto toolchain. The book is the introductory volume in a four-volume graduate sequence:

  • Biostatistics Practicum covers the workflow infrastructure (Git, Docker, renv, Quarto, CDISC, SAS) that surrounds the methods.
  • Statistical Computing in the Age of AI (this volume).
  • Advanced Statistical Computing in the Age of AI covers the advanced material: numerical stability, numerical linear algebra in depth, advanced optimisation, EM, Monte Carlo, MCMC, modern Bayesian computation, high-performance and distributed computing, high-dimensional methods, machine learning, software engineering, interactive visualisation.
  • Applied Generative AI for Health Sciences Research treats generative AI as the orthogonal axis: capability classes, reasoning models, biomedical RAG, multimodal medical AI, agents, evaluation, regulation, deployment.

See the Preface for motivation and the Conventions page for visual cues used throughout.

License

This book is licensed to you under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The code samples in this book are licensed under Creative Commons CC0 1.0 Universal (CC0 1.0), i.e. public domain.