This online collection of tutorials was created by graduate students in psychology as a resource for other experimental psychologists interested in using R for statistical analyses and graphics. Each chapter was created to provide an overview of how to code a particular topic in the R language.

Who is this book for?

This book was designed for psychologists already familiar with the statistics they need to utilize, but who have zero experience programming and working in R. Many of the authors of these tutorials had never used R prior to taking the course in which this collection of tutorials was created. In one semester, they were able to gain enough proficiency in R to independently create one of the tutorials included here.

Tutorial Structure

This website was created with 6 major sections: Programming, Plotting, Regression, ANOVA, Advanced topics,and R-Apps.The tutorials build on each other, but can also be utilized independently from one another, and refer back to other chapters that cover related topics in greater depth.

  1. R-programming: includes 9 chapters which covers the basics of how install R, review of the important basic functions, and some advanced concepts such data manipulation and transformations to prepare your data for analysis.
  2. Plotting: included 2 chapters on how to make pretty plots for the most common uses in psychology.
  3. Regression: included 8 chapters spanning how to conduct different types of regressions (linear, multiple, moderation/mediation,moderated mediation, logistic, Poisson, and multilevel and Mixed). Chapters focus on how to be able to run models and check assumptions. Some have short theoretical reviews.
  4. ANOVA: included 2 chapters on how to run between-, within-, and mixed-subjects ANOVAs with simple set of follow-up tests.
  5. Advanced topics: included 4 chapters on selecting correlation types, AIRMA, decision trees and signal detection.
  6. R Apps: includes a chapter which shows how to make a Shiny application, a living online document which is reactive to user input and a chapter which shows how an ANOVA parses variance.

Some the chapters simulate datasets and others have links for you to download csv files. Each chapter might use different packages (i.e., library of functions), please install.packages("name of package") indicated at the start of each chapter for doing the tutorial. For more information on installing packages see https://www.r-bloggers.com/installing-r-packages/.

Future Updates

We hope this website will grow as more students learn R and contribute. We will also accept chapters from anyone who would like to contribute!


We would like to thank all the authors for working to learn R and sharing their newfound skills with the growing R user community in psychology. We encourage you to explore R for yourself!

  • Alexander Demos & Carlos Salas

For comments, question, and/or corrections please email: ademos@uic.edu

Author List

The authors of the tutorials were all graduate students in the department of psychology at the University of Illinois at Chicago. Below are their names and the divisions to which they are affiliated.

First Last Division
David Abugaber-Bowman Spanish/Cognitive
Mohamad Mowafak Allaham Social
Alyssa Blair Cognitive
Teresa Borowski Community
Emily Bray Community
Timothy S. Carsel Social
Marie Chesaniuk Clinical
Andriana Christofalos Cognitive
Samantha Corwin Behavioral Neuroscience
Jacklynn Fitzgerald Behavioral Neuroscience
Olivia Holmes Social
Ihor Kohut Cognitive
Davi Lakind Clinical
Kirk Manson Behavioral Neuroscience
Matthew McCurdy Cognitive
Zachary J. Melton Social
Allison B. Mueller Social
Michael Palmeri Clinical
Felix Pambuccian Cognitive
Julia Prims Social
David Sarmento Cognitive
Sushmita Shrikanth Cognitive
Callie Silver Community
Erin Sovansky Winter Cognitive
Timothy Sparer Cognitive
Anthony Washburn Social
Kendal Wong Social

We would like to also thank Matthew Andreotta matthew.andreotta@research.uwa.edu.au for helpful comments and edits.