Reproducible Research with R and RStudio
📘 About This Book
Praise for previous editions: "Gandrud has written a great outline of how a fully reproducible research project should look from start to finish, with brief explanations of each tool that he uses along the way... Advanced undergraduate students in mathematics, statistics, and similar fields as well as students just beginning their graduate studies would benefit the most from reading this book. Many more experienced R users or second-year graduate students might find themselves thinking, ‘I wish I’d read this book at the start of my studies, when I was first learning R!’...This book could be used as the main text for a class on reproducible research ..." (The American Statistician) Reproducible Research with R and R Studio, Third Edition brings together the skills and tools needed for doing and presenting computational research. Using straightforward examples, the book takes you through an entire reproducible research workflow. This practical workflow enables you to gather and analyze data as well as dynamically present results in print and on the web. Supplementary materials and example are available on the author’s website. New to the Third Edition Updated package recommendations, examples, URLs, and removed technologies no longer in regular use. More advanced R Markdown (and less LaTeX) in discussions of markup languages and examples. Stronger focus on reproducible working directory tools. Updated discussion of cloud storage services and persistent reproducible material citation. Added discussion of Jupyter notebooks and reproducible practices in industry. Examples of data manipulation with Tidyverse tibbles (in addition to standard data frames) and pivot_longer() and pivot_wider() functions for pivoting data. Features Incorporates the most important advances that have been developed since the editions were published Describes a complete reproducible research workflow, from data gathering to the presentation of results Shows how to automatically generate tables and figures using R Includes instructions on formatting a presentation document via markup languages Discusses cloud storage and versioning services, particularly Github Explains how to use Unix-like shell programs for working with large research projects
📖 Summary
Christopher Gandrud’s Reproducible Research with R and RStudio, published in 2020 across 299 pages, serves as an essential guide for modern researchers, data scientists, and analysts who want to ensure their work is transparent, verifiable, and easy to replicate. In a landscape where computational research underpins crucial decisions in business, economics, and academia, the ability to reproduce findings from raw data to final report is more critical than ever. This third edition brings together the diverse skill sets and software tools required to execute a fully reproducible research project from start to finish. Gandrud provides clear, practical explanations of the tools he utilizes along the way, bridging the gap between raw data analysis and polished academic or corporate reporting. The book addresses the common pitfalls of traditional research workflows, where scattered files, undocumented data manipulations, and manual copy-pasting of results make verification nearly impossible. By leveraging the power of R and RStudio, readers learn how to integrate code, data, and narrative text into a single dynamic document. This approach not only saves time when data updates occur or errors are discovered, but it also builds trust among peers, reviewers, and stakeholders. Throughout the text, the author outlines the foundational components of a robust reproducible workflow, covering version control, automated document generation, data management, and collaborative sharing. Advanced undergraduate students in statistics, mathematics, and related fields, as well as beginning graduate students, will find the structured guidance invaluable. Even more experienced R users and seasoned graduate students often read the book and wish they had encountered its lessons at the very beginning of their studies. The text successfully demonstrates how to maintain organization across complex projects, handle large datasets efficiently, and present findings clearly using modern formatting tools. By adopting the practices detailed in this volume, researchers can streamline their analytical pipelines and contribute to a more transparent scientific community. Whether used as a primary textbook for a dedicated university course or as a self-study reference for working professionals in business and economics, Reproducible Research with R and RStudio equips readers with the technical proficiency and organizational mindset needed to elevate the quality and credibility of their data-driven projects.
🎯 Key Lessons
⚖️ Pros & Cons
✅ Pros
Provides a clear and complete outline of a fully reproducible research project workflow
Combines essential tools and skills into one cohesive resource
Highly beneficial for both students and experienced data analysts
Serves as an excellent main text for academic courses on reproducibility
⚠️ Cons
Requires a foundational familiarity with the R programming language
Rapidly evolving software tools may require supplementary updates outside the text
❓ FAQ
Who is the author of Reproducible Research with R and RStudio? +
The book was written by Christopher Gandrud.
When was this third edition published? +
The book was published in 2020.
How many pages does the book contain? +
The book spans 299 pages.
Who is the primary target audience for this book? +
It is ideal for advanced undergraduate students, beginning graduate students, and researchers in fields like statistics and economics.
Can this book be used as a classroom textbook? +
Yes, it can serve as the main text for a class focused on reproducible research.
