R
Welcome to R, a powerful and beginner-friendly programming language for data analysis and statistics. This guide will help you get started quickly and confidently.
What is R?
R is a high-level programming language and environment designed for statistical computing, data analysis, and visualization. It is widely used in:
- Data analysis and statistical modeling
- Data visualization
- Scientific research
- Geospatial analysis (GIS)
- Reporting and reproducible research
R is especially popular in academia, research, and data-focused fields due to its extensive collection of packages and strong support for statistical methods.
Why Learn R?
- Designed for Data Analysis – Built specifically for working with data and statistics.
- Powerful Visualization Tools – Create high-quality graphs and charts.
- Extensive Package Ecosystem – Thousands of packages for specialized tasks.
- Strong Research and Academic Use – Widely used in science, economics, and social sciences.
- Reproducible Workflows – Tools like R Markdown make it easy to document and share analyses.
Resources for Learning R
In addition to these guides, there are many CSU courses and free resources available for learning R.
View CSU Course Tree
Topic
Prerequisite Group
Course
Here are some of the free resources available organized by category.
Applied / Domain-Specific Resources
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| Brian Gerber: Github | Brian Gerber | Learning to use for loops for simulating purposes | Intermediate |
| Coding and Cookies: R | Coding and Cookies | Accessing introductory R Material and Online resources | Beginner |
| Mike Johnson: Github | Mike Johnson | Building a website using R, as well as accessing R Code for water based applications | Beginner |
| Posit Cloud: R Recipes | Posit | Accessing coding examples of R for learning | Beginner - Advanced |
| R for Spatial Analysis (GitHub) | dcarver1 | Using R for Geospatial analysis | Beginner - Advanced |
| Xinran Wang: Github | Xinran Wang | Learning to built Quarto Websites and apply themes | Intermediate |
Online Coures / Structured Learning Paths
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| Colorado State University: Environmental Data Science Applications: Introduction | Caitlin Mothes | Using R Studio for environmental science applications | Intermediate |
| Colorado State University: Introduction to R Programming | Dharma Hoy | Getting foundational knowledge in R concepts | New to Programming |
| Colorado State University: Mechanical Engineering Data Analysis in R | John Volckens | Introductory concepts of R for mechanical engineering applications | Beginner |
| Colorado State University: Environmental Data Science Applications: Water Resources | Mike Johnson | Learning about water based appilcations of R and Machine Learning | Intermediate |
| Colorado State University: Water Quality Monitoring | Ryan Bailey | Modeling Lake and Stream Water quality | Advanced |
| Colorado State University: Statistical Learning and Data Mining | Stacy Edmondson | Learning how to use R studio for statistical applications in medicine, government, science, and business | Advanced |
| Guarav Jetly: Github | Guarav Jetly | Accessing foundational tools for R through workshop | Beginner |
In Person Courses / Structured Learning Paths
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| Colorado State University: R Programming for Research | Brooke Anderson | Learning R and using it for research purposes | Intermediate |
Books / eBooks
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| Hands-On Programming with R | Garrett Grolemund | Learning programming fundamentals in R | Beginner |
| Introduction to R | Multiple authors | Accessing Foundational concepts and basics of R | Beginner |
| John Volckens: Coursebook | John Volckens | Learning a wide array of R concepts | Beginner |
| R for Data Science | Hadley Wickham & Garrett Grolemund | Acessing R related textbook resources | Beginner - Advanced |
Documentation / Reference / Practice
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| R Packages | Community-driven | Exploring available R packages | Intermediate |
Video Courses / Structured Learning Paths
| Resource | Author / Provider | Best for (goal) | Level |
|---|---|---|---|
| Sage Campus: Introduction to R | Sage Campus | Introducing onself to R | New to Programming |
| Sage Campus: Practical Data Management in R | Sage Campus | Wrangling and managing data for ecological applications | Intermediate |
| The Carpentries: Data Analysis and Visualization in R for Ecologists | Data Carpentry | Data analysis; scientific workflows | Intermediate |