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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

Research Consultant

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 Tutorials even a year old may be **out of date**.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

- Why The R Programming Language Is Good For Business (FastCompany)
- Choosing R or Python for Data Analysis (DataCamp) - From 2015, but still useful
- Where should I start - R or Python? (SAGE campus)
- Python can be better for general tasks, plus data collection and machine learning
- R can be better for analysis, like network analysis and statistics, and visualization

- If you know other
**programing**languages,**Python**will likely be easier to start with. - If you
*instead*are familiar with**statistical**software,**R**will likely be easier to start with. - If you are just starting out,
- Pick
**R**If you will mostly work with**data tables**and be in an**academic**context - Pick
**Python**if you will work with**text**or**websites**and/or be in a**business**context

- Pick

Many people will ultimately learn both. But, they are similar enough that you do not want to learn them at the same time--it can get confusing to switch back and forth. Knowing either one will help you learn the other. So, just pick one and get started!

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: Oct 26, 2022 4:49 PM
- URL: https://infoguides.gmu.edu/learn_r
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