Start by downloading R from the official R website, and then (you don't have to, but it's highly recommended!) download R Studio.
- Tutorial: Getting Started with R and RStudio - "In this tutorial we’ll learn how to begin programming with R using RStudio. We’ll install R, and RStudio RStudio, an extremely popular development environment for R. We’ll learn the key RStudio features in order to start programming in R on our own."
- R for Beginners - "the goal of the present document is to give a starting point for people newly interested in R".
- Introduction to R - notes for an introductory R workshop for Python programmers.
- Introductory R Tutorial
- R Reference Card - R cheat sheet.
- RStatistics.Net - an educational resource for all things related to R language and its applications in advanced statistical computing and machine learning.
- R for Data Science - this is the website for “R for Data Science”. This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualize it and model it. In this book, you will find a practicum of skills for data science.
- Advanced R - the website for work-in-progress 2nd edition of “Advanced R”. The book is designed primarily for R users who want to improve their programming skills and understanding of the language. It should also be useful for programmers coming to R from other languages, as it explains some of R’s quirks and shows how some parts that seem horrible do have a positive side.
- Biomedical Data Science/Data Analysis for the Life Sciences - This book will cover several of the statistical concepts and data analytic skills needed to succeed in data-driven life science research - all in R.
- Intro to Data Science with R - this series is a comprehensive introduction to Data Science using the R programming language.
- What You Need to Know About R - a free ebook, that provides a "first step into the world of R where you will learn about the core concepts, libraries, and packages."
- Introduction to R programming - this is an intermediate/advanced R course appropriate for those with basic knowledge of R. It is intended for those already comfortable with using R for data analysis who wish to move on to writing their own functions.
- Live Interactive Notebook - for the workshop with code examples that you can run and modify in your web browser.
- GitHub Repo for the Workshop
- R Data Management - before data can be used effectively it must often be cleaned, corrected, and reformatted. This workshop introduces the basic tools needed to make your data behave, including data reshaping, regular expressions and other text manipulation tools.
- R Graph Gallery
- Introduction to R graphics with ggplot2
- Live Interactive Notebook - for the workshop with code examples that you can run and modify in your web browser.
- GitHub Repo for the Workshop
- Introduction to Regression Models in R
- Live Interactive Notebook - for the workshop with code examples that you can run and modify in your web browser.
- GitHub Repo for the Workshop
- R Machine Learning Ebook - a free pdf ebook: "With nearly 400 pages of in-depth of tutorials, best practices, and expert insight, this free eBook has everything you need to start using R to build powerful machine learning systems."
- Practical Guide to Implement Machine Learning with CARET Package in R (with practice problem)
- How to use Multinomial and Ordinal Logistic Regression in R ?
- Simple Guide to Logistic Regression in R
- R Deep Learning Essentials - a free ebook tutorial to Deep Learning in R.
- Learning Statistics with R
- An Introduction to Statistical Learning - This book provides an introduction to statistical learning methods. The book also contains a number of R labs with detailed explanations on how to implement the various methods in real life settings.
- The Elements of Statistical Learning - This book is a more advanced book (compared to the previous one), but also a great resource. You can download a PDF version for free.
- Statistical Learning with Applications in R - a YouTube playlist of videos on statistics in R.
- Statistics and R - "an introduction to basic statistical concepts and R programming skills necessary for analyzing data in the life sciences."
- Introduction to Linear Models and Matrix Algebra - learn to use R programming to apply linear models to analyze data in life sciences.