The course uses the R programming language (and several add-ons, so-called “packages”, including ggplot2).

In addition, this course heavily relies on the RStudio software environment to write and execute R scripts and to manage projects. The RStudio IDE (Integrated Development Environment) provides a number of important functions that make using R and ggplot2 easier which we will learn as the course progresses.

Finally, we will make use of a number of R packages from the so-called tidyverse. The tidyverse is a collection of packages that make reading, processing and transforming, modeling, and–most importantly for this course–data visualization much easier and straightforward.

Installation Instructions

Important: I assume that you will have installed or updated the following software and R packages, as we won’t have time during the workshop to do so.

Install R

  1. Download the latest pre-compiled version of R from (both Windows/Mac/Linux binaries are available). The latest R version, as of this writing, is R 3.4.3. If you have R already installed, make sure that it’s version 3.3 or higher. If it’s lower than 3.3 you should update your R version. This can be a bit tricky, but the installr package helps with that. Instructions for updating R with the installr package can be found here:

  2. To install R, execute the downloaded binary and follow the instructions on the screen.

Install RStudio

  1. Download the “Free” version of RStudio at Binaries are available for all major operating systems. If you have RStudio installed, make sure that you’re using RStudio v > 1.0 (to check, open RStudio => Help => About RStudio. In this drop down menu, you’ll also find the option to update directly.)
  2. Execute the binary file and install RStudio following the instructions on the screen.

Install required packages

  1. Open RStudio and type (or copy and paste) the following code into the R console on the lower right corner to install the required packages for the course.
install.packages("tidyverse") # data management and visualization packages, incl. ggplot2
install.packages("readxl") # for reading Excel files
install.packages("haven") # for reading SPSS and Stata files
install.packages("gapminder") # example data sets
install.packages("dotwhisker") # coefficient plots

Make sure your installation works

After following the above instructions, open RStudio (if it isn’t already open) and copy and paste the following into the R console and hit Enter.


test_plot <- ggplot(gapminder, aes(x = year, 
                                   y = lifeExp, 
                                   group = country)) + 
  geom_line(alpha = 0.4) + 


This should produce the following plot: