EDAinR

Learn Exploratory Data Analysis in the browser or locally in your RStudio IDE with interactive tutorials!

Installation

You can install the development version from GitHub with:

#install.packages("pak")
pak::pkg_install("Sydney-Informatics-Hub/usydColours")

#install.packages("devtools")
devtools::install_github("Sydney-Informatics-Hub/EDAinR")

How to run the tutorial

You can start the tutorial with:

learnr::run_tutorial("EDAinR", package = "EDAinR")

How to use the tutorial

This tutorial consist of content along with interactive components for checking and reinforcing understanding. Throughout the tutorials you will find:

• Narrative, figures and illustrations;

• Code exercises that you can edit and execute directly;

• Links and resources...

The tutorial automatically preserve work done within it, so if you work on a few exercises or questions and then return to the tutorial later, you can pick up right where you have left off.

For the trainer

• Introduction slides for the tutorials are here;
• Instructions for adding new tutorials are here.

Code of Conduct

Please note that this package is released with a Code of Conduct. By contributing to this package, you agree to abide by its terms.

References:

• R for Researchers: An Introduction, Tyson S. Barrett, PhD;
• Tidyverse Skills for Data Science, Carrie Wright, Shannon E. Ellis, Stephanie C. Hicks and Roger D. Peng;
• R Software Handbook Evaluation, Statistics, and Methodology - University of Tennessee, Knoxville;
• R for Data Science (2e), Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
• Hadley Wickham's 2014 "Tidy Data" paper in the Journal of Statistical Software