Starting information about the workshop
This workshop takes place on the 18. and 19. of MARCH, 2022.
18. March: 13:00—17:00
19. March: 09:00—17:00 (11:30—13:00 LUNCH)
Place: University of Salzburg, Unipark (Erabzt-Klotz-Straße 1)
Room: 3.206
In this workshop, we will learn the basics of (a) using the free programming language R; (b) how to work in RStudio; (c) how to write and format reports using R Markdown and (d) how to structure R projects in a manner that eases the workflow when working quantitatively, but also facilitates easy reproducibility of the analyses. The workshop is geared towards PhD students interested in working quantitatively and is freely open to any interested faculty as well as MA students. All parts of the workshop will include hands-on exercises. At the end of the workshop, you will also have free time to use your own data, ask me questions and get feedback.
The second part of this workshop is going to deal with open data and reproducibility. One of the most used open data repositories is the Open Science Framework (OSF). Accounts are, of course, free and easy to set up. Under this link you can find a guide on how to create an account. Feel free to browse the website—take a look at other peoples’ repositories: How do they structure their open data? What trends do you see? Do some structures seem to make more or less sense to you? Of course, you don’t have to do this in preperation for the workshop, but it can certainly never hurt!
You won’t explicitely need an OSF account for this workshop, so this step is really entirely up to you. I would, however, highly recommend it—especially because you can store data here. If you create a repository, it is not automatically open to the public. You can store 5GB of data (of whatever type) in a repository, and it is one of the most secure networks for the sciences. You can then create a share-only like or edit link for collaboration. As far as I am aware, there is no limit to the amount of repositories you can create, so you can use this to collaborate—it is absolutely great!
As soon as a repository is open to the public, you then have 50GB of storage on the respective project/repository (since the goal here is, after all, open data/open science). We will go through a few walk-throughs of the website and how you can also store more than 5GBs on a private repository, if you should ever need that.
In general, there is no previous knowledge required to partake in this workshop, but very basic experience with R or RStudio is definitely helpful, as we will be covering the basics relatively quickly.
I highly reccomend, before coming to this workshop, that you read the first chapter of Bodo Winter’s Statistics for Linguists: An Introduction using R if you have not worked with R until this workshop. Even if you don’t work along with the exercises in the book, simply reading the first chapter will give you a feel of what R is as a programming language. And if you are also in need of an introduction to the regression framework, this book is one for you!
Alternatively, I can highly recommend Michael Franke’s An Introduction to Data Analysis, chapters 2.1–2.3, for a beginning look at R.
Participants should leave this workshop with surer footing in the following areas:
The workshop material will be in English, but questions/discussions can be in German.
Since most of the literature I have read hitherto (and most of the existing literature) on the topics we will be covering in this workshop are in English, I personally feel more comfortable speaking and creating the necessary material in English, as I’m not entirely sure I could explain the concepts with the correct vocabulary in German. This is my own personal shortcoming, and I apologize if this is an inconvenience for anyone.