Expert Skills Training the LBG Career Center
January 31 & February 6, 13 & 20 2025, 10am-12pm, online
My name is Hannah Metzler, and I am currently a PostDoc at MedUni Vienna and the Complexity Science Hub Vienna. I have a background in Psychology and Cognitive Neuroscience, and I currently do research in computational social science at the interface of Psychology and Data Science.
Email: metzler[at]csh.ac.at
Website: https://hannahmetzler.eu
This course will introduce you to coding your data analyses and data visualizations with the software R. It is geared for people who know the basics of statistics, but have never written code before. We will set up R, Rstudio and Git, learn how to wrangle and clean data, how to make pretty plots, and how to do basic statistics (descriptives, t-tests, ANOVAs, regressions etc.) in R. Because it's best to do this from the start of your coding career, you will also learn the basics of version control and backing up your code with Git and Github.
If you have had doubts if you'd be able to write code, but secretly have been wanting to for a long time, this course is for you. In my experience, it seems more challenging and less fun initially than it later turns out to be! Coming from a social science background myself, I want to help others jump over the barrier of self-doubts and make it easy for you to start writing your own code.
- Introduction slides
- Lesson 1: Basics of the Rstudio interface and coding
- Preparation for Lesson 2. Please follow this to setp up Git and GitHub before our next session.
- Lesson 2: Basics of data analysis: Commit & push to Git, read in and manipulate data, make a figure, make a Quarto Document.
- Lesson 3: Linear regression (including Git, plots, data cleaning, Quarto Document)
- Lesson 3 extension: Here, I introduce more data wrangling functions, calculate a t-test, and an ANOVA. This is based on the same analysis project as lesson 3.
As an example for what you can do with Quarto files, here is the code I used to create the above course materials:
This work is licensed under Creative Commons Attribution-ShareAlike 4.0 International License. (CC-BY-SA 4.0).
This course is based on a free online course book and a free online course:
- Lisa DeBruine & Dale Barr. (2022). Data Skills for Reproducible Research: (3.0) Zenodo. <www.doi.org/10.5281/zenodo.6527194>.
- Page Piccinini. (2018). R Course "R for Publication", https://pagepiccinini.com/r-course/.
You can use these resources to repeat lessons, to understand something better, and to continue learning about R.
There are a variety of other free online classes on R, some including an introduction to statistics. You can find a list of courses I have found useful here. If a course has not been updated recently, it is quite likely that some things have changed, as R and its packages are regularly updated. Most things will still work, however.