A series of free and interactive tutorials to R

Welcome to the DCU R Tutorials. This short course will teach you the basic syntax and vocabulary used to code in R. These tutorials are focusing on the Tidyverse R coding style as it is the best to start in my opinion. At the end of these tutorials you will be able to clean and transform a data set, as well as creating fancy visualisations using R.

Chapter 0: Getting Started

This chapter is a quick introduction to how the tutorials work. It also builds your own interactive session which is essential to start.

Chapter 1: WaRm Up

This chapter introduces the basic concepts of R syntax such as arithmetic operations, logical operations, object assignment, vectors and functions.

Chapter 2: Data Transformation

This chapter introduces the basic concepts of R tidyverse syntax such as filter, select, mutate, summarise and more importantly how to use the pipe operator %>%.

Chapter 3: Data Visualisation

This chapter introduces the basics concepts of the {ggplot2} package for data visualisation in the tidyverse.

Chapter 4: Hypothesis Testing and Linear Regression

This chapter introduces the basics concepts of hypothesis formulation and testing with linear regression models.

Chapter 5: Coding R with RStudio to Create Academic Outputs

This chapter introduces the basics of RStudio and RStudio Cloud to produce academic outputs with Rmarkdown files.

About this course

This tutorial uses contents and examples from the following free online books. They are perfect for beginners, feel free to check them out for further information: R for Data Science by Wickham and Grolemund (2017), A ModernDive into R and the tidyverse by Ismay and Kim (2019), Learning statistics with R by Navarro (2019), Introduction to Open Data Science by the Ocean Health Index Team (2019), Getting Used to R, RStudio, and R Markdown by Kennedy (2019) and Statistical Thinking for the 21st Century by Poldrack (2020).

About me

Ph.D in Social and Experimental Psychology from the University Grenoble-Alpes, France, my researches are focusing on understanding psycho-physiological responses ‘in the wild’. Now Assistant Professor of Business Research Methods at Dublin City University, my domain of expertise relies on multivariate time series analysis and trend extraction for supervised or unsupervised machine learning classification.