The goal of the workshop is to teach best practices for data analysis and visualization with R. R is commonly used in many scientific disciplines for statistical analysis and for its powerful data science packages. Known as tidyverse, a collection of R packages allows novice programmers to write clear, concise and powerful code for data analysis and visualization. In this workshop, you will gain hands-on experience on using some of the tidyverse packages to analyze a data set and plot publication-quality graphs. No prior knowledge of the skills or tools is necessary. You should bring a laptop with R and RStudio installed.

At the end of this workshop, you will be able to:

• navigate through a project folder using RStudio;
• install different R packages and learn how to use specific functions from a package;
• read data files with R;
• inspect, clean and modify data sets;
• apply a simple statistical analysis;
• generate publication-quality graphs.

Couldn't install R or RStudio?

• First, you should install R. See the instructions.
• Then, you need to install RStudio: Click here, choose RStudio Desktop (Open Source License), and then simply follow the instructions. Default options should be just fine!

Don't like reading instructions?

Watch these videos: for Windows and for macOS.

• Create a folder named Rworkshop.

• Go to the data folder and download the gapminder.txt file into this folder.

• Go to the scripts folder and download the hands_on_demo.R into the Rworkshop folder.

• Follow the instructor's instructions.

Note that you will find a subfolder named solutions inside the scripts folder, in this Github repo after the workshop, that includes the detailed solutions to the demo and exercise.