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The isdsTutorials package contains a series of interactive tutorials that teach alongside chapters of the free Introduction to Statistics and Data Science textbook. The tutorials are written using a package called learnr. Once a tutorial is running it’s a bit like reading a book but with places where you can practice the R code that you have just been taught along with multiple choice comprehension check questions. The isdsTutorials package is free and offered to support teachers and students using the textbook who want to learn R.


Install the latest version of isdsTutorials from GitHub with the remotes package.

{r} # install.packages("remotes") remotes::install_github("NUstat/isdsTutorials", dependencies = TRUE)

List of tutorials

The tutorials are named sequentially and correspond to the recommended material covered in a single class. The relevant sections of the Introduction to Statistics and Data Science textbook are listed alongside each tutorial.

name content name content
01_intro Preface & Chapter 1 11_regression4 Chapter 6.2 - 6.4
02_ggplot1 Chapter 2.0 - 2.3 12_randomization Chapter 7
03_ggplot2 Chapter 2.4 - 2.6 13_generalizability Chapter 8
04_ggplot3 Chapter 2.7 - 2.9 sample_exam2 Sample Exam 2
05_wrangling1 Chapter 3.0 - 3.3 14_sampling1 Chapter 9.0 - 9.1
06_wrangling2 Chapter 3.4 - 3.6 15_sampling2 Chapter 9.2 - 9.3
07_tidy Chapter 4 16_sampling3 Chapter 9.4 - 9.6
sample_exam1 Sample Exam 1 17_ci Chapter 10
08_regression1 Chapter 5.0 - 5.1 18_pvalues Chapter 11
09_regression2 Chapter 5.2 - 5.4 19_hypothesis Chapter 12
10_regression3 Chapter 6.2 - 6.4 sample_exam3 Sample Exam 3

Running tutorials

There are two ways to run the tutorials. The recommended way to run a tutorial is to type the following line in the R console:

learnr::run_tutorial("01_intro", package = "isdsTutorials")

This should bring up a tutorial in your default web browser. You can see the full list of tutorials by running:

learnr::run_tutorial(package = "isdsTutorials")

Alternatively, in Version 1.3 onwards after having executed library(isdsTutorials), a list of tutorials appears in a tutorial tab (by default it will be in the upper-right pane). However, the print option is not executable if the tutorial is run through the tutorial tab.

Submitting tutorials

After completing each tutorial, students can obtain their grade in html format. Students can then upload the html grade to a learning management system like Canvas or Gradescope.


This work was produced with support from Northwestern University Libraries, with funding from Northwestern University’s Affordable Instructional Resources initiative, and funding from the Open Educational Resources (OER) grant.


Aden-Buie G, Chen D, Grolemund G, Rossell Hayes A, Schloerke B (2023). gradethis: Automated Feedback for Student Exercises in ‘learnr’ Tutorials.,,

Aden-Buie G, Schloerke B, Allaire J, Rossell Hayes A (2023). learnr: Interactive Tutorials for R.,

Sass D (2023). tutorialExtras: Custom questions and exam functions for learnr tutorials. R package version,

Tipton, E., Kuyper, A. M., Sass, D. K., Fitzgerald, K. G., Ismay, C., & Kim, A. (2020). “Introduction to Statistics and Data Science”. Northwestern Libraries Digital Publishing,