Resources to learn and use the Open Source Statistical software R (R-Project)

- Overview
- General Tutorials
- Statistical Analysis
- Data Management
- Graphics
- R Programming
- Good Practices
- Get Help

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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 Tutorials even a year old may be **out of date**.

- Overview
- General Tutorials
- Installing R / GUIs - Start here for online tutorials, plus installation and introductions
- Finding & Installing Packages - Find a package that has functions to make R do almost anything
- Concepts - Learn about the main parts of R syntax and key terms

- Statistical Analysis - See materials for teaching and learning statistics with R
- Data Management - Go here for packages and tutorials on preparing data
- Graphics - R excels at making graphics, see the many options and galleries
- R Programming - Links for programmers who want to know R well
- Good Practices
- Get Help - Need more help? See your options

If you already know another statistical software or programming language, you might try these first.

- R language for programmers by John D. Cook
- MATLAB, NumPY, Julia and R Side-by-side reference sheet - Hyperpolyglot
- Python → R: Introduction to R
- MATLAB → R: MATLAB® / R Reference, by David Hiebeler
- Stata → R: R for Stata Users (Uses R-Commander. Useful glossary/comparison of codes , p. 497)
- Data manipulation in R for Stata users - (Quick reference guide)
- Getting Started in R/Stata pdf (side-by-side tutorial)

- Last Updated: Mar 3, 2020 1:05 PM
- URL: https://infoguides.gmu.edu/learn_r
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