Modern R in Practice
From Analysis Scripts to Reliable Deliverables
Title page
A practical book for R users ready to develop their analysis and delivery skills.
Move from repeated scripts to reusable functions, from a single chart to a report or application that others can use, and from “it runs on my machine” to code that can be tested and traced. These transitions organize the book: technical choices serve a concrete analytical task.
Author: Jaime Yan · Online practice edition
Read the preface Choose a reading path Start the companion lab
Four units, one focus on delivery
| Unit | Question you will address | Expected outcome |
|---|---|---|
| Complex analyses | How do you turn mixed data sources and repeated scripts into a clear, reliable analysis? | Reusable data-processing functions, tables, and plots |
| Professional deliverables | How do you put results into the hands of the people who need them? | A report, dashboard, or interactive application |
| Package development | How do you make code maintainable, testable, and shareable? | An R package with documentation and tests |
| AI and domain applications | How do you evaluate AI assistance and address requirements in specialist settings? | An AI workflow with explicit checks and domain examples |
Prerequisites
You should be able to read a CSV, filter and summarize data, create a basic ggplot, and understand function calls and pipes. With those skills, you can start at the first chapter. Readers in clinical research and pharmaceuticals can also follow the domain reading path.
For a refresher, read the Whole game section of R for Data Science, second edition, then import, tidy, and plot a dataset of your own. You do not need prior experience with package development, Shiny, or LLM APIs.
Book, practice, and reference library
The chapters follow learning outcomes; the companion lab supplies tasks and acceptance criteria; the conference catalog provides access to the original workshops. You can read this book without browsing the catalog first.
posit::conf workshops are an important source. Other books and official documentation provide conceptual support and further reading. Each chapter retains a SOURCES section. See Further reading for additional resources and Authorship and acknowledgments for the distinction between the book author and its source authors.