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Software for Data & Digital Scholarship

Information about DiSC-supported software for the collection, processing, analysis or display of numeric, text, or geospatial data

The R Project for Statistical Computing is a free, open source statistical computing language that is popular among researchers in many fields. 

The learning curve for true understanding is steep, but specific tasks (e.g., importing files from other statistical software) are often quite easy because of packages that can be created by anybody. R undergoes rapid development and improvement. Tutorials even a year old may be out of date. 

NOTE: RStudio is currently in the process of changing names to Posit. Various tutorials may reference one or the other, but both are acceptable at this time.

Access to R & RStudio

Start Here

Installing R and RStudio

NOTE: RStudio is now Posit (Both names are being used). The RStudio / Posit website undergoes frequent changes so the process of downloading RStudio will be slightly different. But, the links/buttons use the same names (and have blue backgrounds to stand out).

Integrated Development Environments

Literate Programming

Instead of creating a "script" file with R code, and producing output in separate files, you can combine them. Also called "notebooks", there are several methods that allow you to combine code and text (using a markup language like Markdown).

  • Jupyter Notebook
  • RStudio Quarto Document & Visual Editor
    • Quarto Visual Editor [Part 1] (~10min, Andy Field)
    • Quarto provides more features, including a visual editor and multi-language support. If your instructor asks you to use R Markdown, the Quarto video will still be useful. Or, you might politely ask your instructor if you can submit a Quarto document instead, as they may not know about this new feature.
  • RStudio R Markdown Document

R Infoguide

Learn R Infoguide: Table of Contents

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