R is a statistical programming language which has emerged as an important modern data science tool, in academia and beyond
It is open source and freely available, platform independent, extremely powerful for statistical analysis and visualisation and backed by a substantial ecosystem of packages and a large, vibrant community of developers and contributors. The scripted nature of performing analyses in R also contributes to transparency and reproducibility and makes analyses easier to share and easier to build on.
This course will start with the basics of working in R as well as introduce basic programming concepts like iteration, writing functions and controlling execution flow. We'll then dive into using R for data analysis, focusing on what consists of 80% of work involved in analysing data, data wrangling. We'll focus on using packages in the tidyverse for reading in, manipulating, combining, analysing and plotting data. We'll also look at literate programming through Quarto, i.e. the process of combining code, text and results of code execution in a single document to produce shareable reports. Throughout all, we'll also introduce best practices for working with R projects with a focus on reproducibility.
- Introduction to basics of R.
- Programming in R: iteration, controlling execution flow, functions.
- Data wrangling in R with the tidyverse.
- Literate programming with Quarto.
- Best practices in working with R projects.
Continuing Professional Development (CPD)
This event is approved by the Royal Society of Biology for purposes of CPD
and may be counted as 60 CPD credits
For full details and to register, visit the Marine Biological Association website