Effectively handling, processing and analysing large amounts of data is an essential skill for modern evolutionary biologists. Large genomic and phenotypic datasets are now routine for the biosciences and we are no longer at point where a simple desktop program can suit our needs for data curation, statistical analysis and visualisation. To meet the challenge, it is necessary for biologists to learn how to program and the fundamentals of data science. As well as this, exploring, visualising and understanding data in a programming environment can help reinforce understanding of key concepts and mathematical or statistical relationships.

These reasons are the motivation for the online sections of our book, Evolutionary Genetics: Concepts, Analysis & Practice. Each of the ten tutorials hosted here are self-contained introductions to key concepts in evolutionary genetics and they are also designed to familiarise you with the basics of the R programming language. You can follow them as a practical course in both R programming and evolutionary genetics, or you are free to choose the tutorials you are most interested in and to explore them. Each tutorial comes with a set of study questions which you can use to reflect on your learning and of course, we also provide the answers for you to check your work against.

The first two tutorials (Chapters 1 & 2) are genetics-free, providing an introduction to R and also the tidyverse approach. They are intended for as wide an audience as possible. We hope they will be of use to biologists and non-biologists alike.

Mark Ravinet & Glenn-Peter Sætre Oslo, October 2018

Practicals and exercises