Free Resources for Learning R

Many Statistical Horizons and Code Horizons seminars now use R as their primary computational platform for examples and exercises. Those seminars include:

• Advanced Machine Learning
• Analysis of Complex Survey Data
• Analyzing Text Data Using Sentiment Analysis
• Applied Bayesian Data Analysis
• Applied Bayesian Data Analysis: A Second Course
• Categorical Data Analysis
• Causal Inference in Econometrics
• Causal Mediation Analysis
• Data Visualization Using R
• Data Wrangling with R
• Design and Analysis of Simulation Studies
• Difference in Differences
• Experimental Methods
• Exploratory Factor Analysis
• Exploratory Graph Analysis with R
• Extracting and Analyzing Web and Social Media Data
• Interpreting and Communicating Statistical Results with R
• Introduction to Social Network Analysis
• Introduction to Statistical Genetics
• Introduction to Structural Equation Modeling
• Introduction to Text as Data
• Item Response Theory
• Latent Growth Curve Modeling
• Longitudinal Data Analysis Using R
• Machine Learning
• Machine Learning for Estimating Causal Effects
• Matching and Weighting for Causal Inference with R
• Missing Data Using R
• Missing Data Using R (for students)
• Multilevel and Mixed Models Using R
• Nonparametric and Semiparametric Statistics
• Power Analysis and Sample Size Planning
• Propensity Score Analysis: Advanced
• Propensity Score Analysis: Basics
• Psychometrics
• R for SPSS Users
• Regression Discontinuity Designs
• Reproducible Reports with Quarto and R Markdown
• Sample Size Justification
• Sensitivity Analysis for Causal Inference
• Social Networks: Statistical Approaches
• Statistics With R
• Structural Equation Modeling Done Right
• Survival Analysis Using R
• Time Series Analysis
• Using Large Language Transformer Models for Research in R
• 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 livestream 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? In that case, our first recommendation is to watch a one-hour video that was prepared especially for participants in our seminars:

A BRIEF INTRODUCTION TO R

In this video, Professor Stephen Vaisey, Director of Code Horizons, walks viewers through the basics of R and RStudio .

WEB BOOKS

If you prefer a text-based introduction, the web is full of resources for learning R. But 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.

MODERN DIVE

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.