Free Web Books for Learning R
Many Statistical Horizons seminars now use R as their primary computational platform for examples and exercises. Those seminars include:
- Applied Bayesian Data Analysis
- Building Web Apps with R Shiny
- Data Visualization
- Data Wrangling with R
- Experimental Methods
- Longitudinal Data Analysis Using R
- Machine Learning
- Matching and Weighting for Causal Inference with R
- Multilevel and Mixed Models Using R
- Power Analysis and Sample Size Planning
- Social Networks: Statistical Approaches
- Text as Data
- Workflow of Data Analysis Using R
There are lots of good reasons to learn R, even if it won’t be your main statistical package. One excellent way to do that is to take our remote seminar, Statistics with R. But what if you want to learn just enough R to feel competent and comfortable in one of our R-based seminars? Although the web is full of resources for learning R, finding the right one isn’t easy.
Good news! We’ve done the work for you. After scouring the web, we have identified three online books that we think do a terrific job of giving you the knowledge and skills you need to participate in our R seminars. And like R itself, they’re absolutely free.
YaRrr! The Pirate’s Guide to R
This accessible (and playful!) guide is oriented to behavioral scientists and will get you analyzing data right away. Working through chapters 2-4, 9, 13, 15 will prepare you for most of what you will encounter in a Statistical Horizons R course. Don’t be put off by the pirate theme. This book is packed with useful information that’s quick and easy to digest.
Click here to read YaRrr! The Pirate’s Guide to R.
This online book provides a balanced introduction to R with a strong emphasis on data wrangling and visualization. After going through the first two parts, you would be ready for any of our R courses.
Click here to read Modern Dive.
R for Data Science
This is the gold standard for developing R programming, data management, and visualization skills. This book has many short chapters. Even just going through chapters 2-6 would give you a basic familiarity with R.
Click here to read R for Data Science.