In this one day workshop, we will provide a friendly but comprehensive introduction to R. It is intended to provide people who are new to R with all the basics and fundamentals that they need to get up and running with R so that they can use it on a regular basis. We will provide an introduction to R fundamentals such as an overview of RStudio, R commands and operations, assignment, data structures, functions, scripts, packages, reading in data files, viewing and summarizing data, and data visualization using ggplot2. We will also cover how to do statistical data analysis in R, particularly linear regression and Anova models.

Schedule

• 09:30-09:50 What is R, and why should we care?
• 09:50-10:10 Installation and setup
• 10:10-10:30 Guided tour of RStudio
• 10:30-11:00 Basic R commands and workflow
• 11:00-11:15 Break
• 11:15-11:30 Working with data (reading-in, viewing, summarizing data)
• 11:30-11:45 Basic plotting and visualization
• 11:45-12:30 Basic statistical analyses (linear regression, anova, t-tests, correlations)
• 12:30-13:30 Break
• 13:30-14:30 More working with data (the tidyverse way, i.e. using https://dplyr.tidyverse.org/ and https://tidyr.tidyverse.org/)
• 14:30-15:30 More data visualization (learning to love ggplot)
• 15:30-16:30 More statistical analyses (including logistic regression, multilevel models)

Installing the necessary software

The required software for these workshops are all free and open source and will run identically on Windows, Mac OS X, and Linux platforms.

There are four main pieces of software to install:

• R: An environment for statistical computing.
• Rstudio: An integrated development environment for using R.
• tidyverse: A bundle of R packages to use R the modern way.
• Miscellaneous R packages: Other vital, or just handy, R packages.

GitHub resources

Further resources for this training course can be found on Github at mark-andrews/introduction-to-R.