Git and GitHub for Biostatistics
A One-Week Boot Camp for incoming graduate students
Welcome
This is the online version of Git and GitHub for Biostatistics: A One-Week Boot Camp by The rgtlab Curriculum Project, a short preparatory course for incoming graduate students in biostatistics and adjacent programs.
The book covers everything an entering masters-level biostatistician needs to place their analytical work under version control on day one of the academic program: installing and configuring Git, recording a project’s history in commits, navigating and undoing that history, branching and merging, publishing to GitHub, and collaborating through pull requests. It is designed for five consecutive days of work: one hour of lecture content each day, two hours of homework, no examinations.
The organizing principle is that version control is a research-integrity tool, not a software-engineering nicety. A biostatistician who cannot say which version of a script produced a published table has a reproducibility problem, not a tooling preference. Every chapter opens with a data-analysis problem, develops the Git mechanism that addresses it, and returns to the problem to judge what the mechanism did and did not solve.
The boot camp is a preparatory companion to a five-volume graduate sequence:
- R for Biostatistics: A One-Week Boot Camp (https://r-bootcamp.rgtlab.org), the parallel preparatory volume for R.
- Biostatistics Practicum, workflow infrastructure (Git in depth, Docker, renv, Quarto, CDISC) that builds directly on this boot camp.
- Statistical Computing in the Age of AI, introductory methods (linear models, GLM, mixed models, survival, Bayesian, bootstrap, simulation).
- Advanced Statistical Computing in the Age of AI, advanced computing (numerical stability, MCMC, HPC, high-dimensional methods, ML, software engineering).
- Applied Generative AI for Health Sciences Research, capability classes, RAG, agents, evaluation, regulation, deployment.
Together with R for Biostatistics, this volume forms the two-part pre-program preparation: one week of R, one week of version control. A student who completes both arrives at the Practicum ready to work in a reproducible pipeline from the first session.
See the Preface for the design rationale and the Conventions page for visual cues.
License
This book is licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International.
Code samples are licensed under Creative Commons CC0 1.0 Universal, i.e. public domain.