Yes, because A to Q are silly, we skip right over to R. R is a free and open-source programming language for statistical analyses.

Sounds boring? It can do visualizations too! And interactive visualizations, even animations, if you fancy. It can do documents with integrated code and output (this syllabus was written in R). And it can even do presentations, journal articles, books, websites, what not!

Well, there’s a lot it cannot do. For one, it won’t do your dishes. And you’ll have to learn to program. That’s doing your analyses without a mouse; just you and the keyboard.

In return, you’ll be able to use the most popular and most powerful statistical software presently available. Its community built over 15000 extensions that are free for you to use. Ever wanted to perform a Bayesian binomial SEM ninja analysis with adaptive non-parametric splines? R can do, probably. As well as an ANOVA.

As well as ASCII art (code is shown with output directly below it):

cowsay::say("We R Champions")

We R Champions 
          ==) ^Y^ (==
            \  ^  /
            /     \
            |     |
           /| | | |\
           \| | |_|/\
      jgs  //_// ___/

Want to use R? It’s simple. Sign up for our R Masterclass Series and start learning.


The series includes several modular masterclasses, on data analysis, data transformation, data visualization, data communication, and reproducibility.

  • Instructors: Alexander Savi and Simone Plak.
  • Lingua franca: Dutch or Dunglish, depending on the participants.
  • Sign up: you’ll receive a sign-up link in your mail. Drop us a line if you want to be sure to get it.


The We R Champions masterclass series includes several masterclasses (that’s why we call it a series, don’t tell anyone, it’s a secret). There are fundamental, recommended, and nerd masterclasses (see color coding below). After each masterclass, you’ll walk away with the R software installed and a personal R script that you can use to reproduce everything that was covered. In the sections below, we go over the contents of each of them.

Note that the recommended and nerd masterclasses are conditional on sufficient interest and available time.

We R Novices

In We R Novices you’ll learn..

  • how to set up R
  • what R can be used for
  • how to use RStudio Desktop
  • how to use good programming habits (projects, scripts, comments)
  • how to navigate through R space (packages, vignettes, cheat sheets, Q&A)
  • how to continue to learn and use R on your own
  • how to use R without having to program

In We R Novices you’ll NOT learn..

  • base R. Or at least not all of it. Because even though it’s the basis, it’s advanced. You’ll be able to learn it in the We R Programmers masterclass.
  • how to do data analysis. You’ll learn it in the follow-up We R Analysts masterclass.
  • how to get your data transformed and tidied. Instead, use your favorite data editor or learn how to do it in R in the We R Transformers masterclass.
  • how to create figures. Becoming an artist takes more than an hour, but you’ll be able to learn it in the We R Visualizers masterclass.
  • how to become an R ninja. Take the We R Reproducible, We R Publishers, and We R Programmers masterclasses to become a Master of Rts.

We R Analysts

In We R Analysts you’ll learn..

  • how to import data from Excel, SPSS, SAS, Stata, and R, using the readr, haven, and readxl packages
  • how to compute descriptive statistics
  • how to perform basic statistical analyses
  • how to check common assumptions

We R Transformers

In We R Transformers you’ll learn..

  • how to transform and tidy your data for your specific needs, using the tidyr and dplyr packages
  • how to transform date variables, time variables, text variables, and factor variables, using the lubridate, hms, stringr, and forcats packages

We R Visualizers

In We R Visualizers you’ll learn..

We R Reproducible

In We R Reproducible you’ll learn..

  • how to get from raw data to your final maniscript, and be reproducible
  • how to use version control with Git and GitHub
  • how to write reader-friendly R prose using R style
  • how to write share-friendly R code using projects, and packages like here and renv

We R Publishers

In We R Publishers you’ll learn..

  • how to integrate code, output, and text (like in this syllabus)
  • how to make presentations in R
  • how to create and publish interactive applications with R Shiny
  • how to write and publish journal articles and books with R
  • how to build websites with R
  • how to check your manuscripts, using the statcheck and retractcheck packages

We R Programmers

In We R Programmers you’ll learn..

  • base R
  • how to write explicit and implicit loops
  • how to write your own R functions
  • how to build your own R packages
  • how to run simulations



You get two for the price of one.

  • Alexander Savi (contact) taught Basic Skills in Statistics (in R) and Programming The Next Step. He has over ten years of R experience.
  • Simone Plak (contact) taught Programming in Psychological Science (in R). She has over six years of R experience.

Both of us have lots of R experience and don’t get angry easily, so you’ll be in good hands.


The masterclasses are modular. Don’t know where to start? The graph below shows the recommended order to take the masterclasses.

masterclass_recommendation <- data.frame(
  from = c("We R\nNovices",
           "We R\nAnalysts",
           "We R\nTransformers",
           "We R\nVisualizers",
           "We R\nReproducible",
           "We R\nPublishers"),
  to = c("We R\nAnalysts",
         "We R\nTransformers",
         "We R\nVisualizers",
         "We R\nReproducible",
         "We R\nPublishers",
         "We R\nProgrammers"))

qgraph::qgraph(masterclass_recommendation, layout = "circular")