Email: Andrew.Stewart@manchester.ac.uk
Twitter: @ajstewart_lang
Slides for my 2019/20 MSci Reproducible Data Science unit. Click on the 'Clone or download' button in the top right to download a zipped version of this repository.
Classes start Friday November 8th and run until Friday December 13th.
The morning session is 1100-1300 and the afternoon session is 1400-1600 in Stopford PC Cluster 3.
Each folder contains the slides in .pdf format, R scripts, all the data, and the worksheets associated with each of the 6 workshops.
Workshop 1 - Reproducibility and R
Workshop 2 - The General Linear Model (Regression)
Workshop 3 - The General Linear Model (ANOVA)
Workshop 4 - Mixed Models
Workshop 5 - Data Simulation and Advanced Data Visualisation
Workshop 6 - Reproducible Computational Environments and Presentations
You will probably want to bring your laptop for this course (although we will be in a PC cluster in case you don't have a laptop). Beforehand, on your laptop you should install R (the language) and RStudio (the interface that helps us interact with R) - each is available for OSX, Windows, and various flavours of Unix. You can install R from here:
https://www.stats.bris.ac.uk/R/
And RStudio from here:
https://www.rstudio.com/products/rstudio/download/#download
You can also access the workshop content and run everything using RStudio via the RStudio Cloud. I have set up our space here:
and have put together a brief tutorial on using it here:
Below are some helpful R resources - it would be useful to look at the first one before the workshop.
This is a very clear and focused introduction to R, RStudio, and R Markdown. You probably want to read the first four chapters sooner rather than later...
This is the online interactive version of the book of the same name. It's a great book to introduce you to data science, reproducibility, and R.
You can run the R scripts for this unit in your browser by launching the unit in a Binder (click on the button below). Once loaded, click on the .Rproj file associated with the workshop you want to go through. That will set the directory to point to the data files.
To join the University of Manchester R User Group, subscribe to the mailing list https://listserv.manchester.ac.uk/cgi-bin/wa?A0=RUM or send an email to LISTSERV@listserv.manchester.ac.uk with no subject and the body SUBSCRIBE RUM Your Name.
Sign up for our Open Science Working Group email list here.