The UNSW School of Biological, Earth & Environmental Sciences & Stats Central introduction to data manipulation and visualisation in R (INTERMEDIATE)
This repository contains content for a 2-day course for HDR students (and other interesting people), run jointly by the School of Biological, Earth & Environmental Sciences (BEES) and Stats Central at the University of New South Wales.
In this course, we teach participants techniques for
1. Conducting reproducible research, and 2. Scaling up their computations.
The techniques we cover under reproducible research empower researchers to
- enjoy coding and feel confident in their results,
- easily generate updates as needed,
- collaborate effectively,
- enhance the transparency of their results, and
- publish their code.
When it comes to scaling up, we look at how to get R to repeat tasks (possibly with different inputs) in an efficient way and organise the output. This general skill is needed in diverse contexts, such as processing lots of files (e.g. from imaging or surveys), working with large datasets, runnign many models, or running simulations (statistical or individual-based). In these circumstances, you'll often find yourself having to repeat the same thing over and over and it's good to learn how to get R to do this in an organised and efficient manner. We'll introduce a series of powerful tools, all which take a bit of instruction and practice to master.
We aim for this workshop to be interactive and involve participants in indetifying the challnges and solutions. It's easy to stand up and tell them evrything, o r give them a manual, but this doesn't necessarily lead to good learning outcomes and doesn't warrant an in-person course. Through discussion, problem solving, and live coding, we aim to
- activate participants minds for learning
- model live collaboration, coding, and problem solving,
- give hands on practice at the techniques we want them to pick up, and
- make the experience two-way and interactive, thereby inviting enw connections to be formed.
Further details on the content are in files
- Day_1_reproducible_research.qmd
- Day_2_scaling_up.qmd
What to bring:
- Laptop with relevant installations (see below) & charger
- Water bottle & food
- Determination, kindness, and a sense of humour.
What software to install / prepare prior to arrival?
- R version 4.2 or newer (https://cran.rstudio.com/).
- The tidyverse library (https://www.tidyverse.org)
- Rstudio (https://posit.co/download/rstudio-desktop/). Note, R and RStudio are different pieces of software so please update Rstudio.
- Github Desktop https://github.com/apps/desktop. Installing git may require extra components, depending on your machine.
- If you haven’t already, please create an account with GitHub.com. We recommend using your UNSW or institutional ID as the primary email, so you can register for an education account (optional).
Note, this repo is intended for instructors. It is where we organise our materials. It is not intended that you circulate this to participants. Rather, our suggestons it tha you collaboratively build a repo of notes and techniques with participants, live, during the workshop. this will mdoel collaboration via git and github, and can involve participants contribtuing.