R for Reproducibility
Preface
This web-book will serve as a full-length version of the materials for the course ‘Open Science Practices: Implementing a Reproducible Workflow in R’. Until it is up-and-running, the slides can be viewed at the following link: https://daniela-palleschi.github.io/r4repro_SoSe2024/
This web-book is the companion to the course ‘Open Science Practices: Implementing a Reproducible Workflow in R’ (and other iterations) given by Daniela Palleschi at the Humboldt-Universität zu Berlin. The tools discussed in this book are specific to the R enviornment, but the concepts are universal and programming language agnostic.
Aims of the book
- introduce students to basic concepts of reprodubility and replication in the scope of language research
- teach students how to implement a self-contained project-oriented analysis workflow
- help students develop good habits for project/data management
- teach students how to write up analyses for a paper or thesis using dynamic reports
- introduce students to concepts like version control and containerization
What you will not learn in this book
- how to analyse data
- how to fit models
- how to plot data
- how to design an experiment
About this book
This book was created using a Quarto Book RProject. The glossary for each chapter was created using the glossary package (DeBruine, 2023). The source code for each chapter is viewable by clicking the <> Code button at the top right of the page. The source code for the whole book is also available via GitHub, and is fully reproducible.