This lesson is still being designed and assembled (Pre-Alpha version)

R for health scientists

Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with health data in R.

This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R.

These lesson are based on “Data Analysis and Visualization in R for Ecologists” by François Michonneau & Auriel Fournier (Lesson Maintainers)


Data Carpentry’s teaching is hands-on, so participants are encouraged to use their own computers to ensure the proper setup of tools for an efficient workflow. These lessons assume no prior knowledge of the skills or tools, but working through this lesson requires working copies of the software described below. To most effectively use these materials, please make sure to download the data and install everything before working through this lesson.


You must have the latest versions of R and RStudio installed


Setup Download files required for the lesson
00:00 1. Before we start
00:00 2. Introduction to R
00:00 3. Starting with data
00:00 4. Manipulating, analyzing and exporting data with tidyverse
00:00 5. Data visualization with ggplot2 How can I create publication-quality graphics using ggplot2?
00:00 6. Reproducible Reports with RMarkdown How can I make reproducible reports in R?
00:00 7. 06 Capstone
00:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.