This is a repository containing the course notes and worked examples for a six week course in the R statistical programming language taught at the University of Melbourne, Australia. It is targeted at graduate students and faculty in psychology (and probably other social sciences) with no programming experience, and covers the use of R from the basics up to multilevel modelling, though it is not exhaustive within that range.
While I taught this course live, I also designed it with self-teaching in mind. Starting in Week 1, reading through the Introduction to R handout will get you started using R with no previous experience. From there, each week contains R files that teach the relevant content and then have worked exercises to test it. I suggest downloading this repository and opening each .R file within RStudio (which you'll understand after reading the Introduction to R handout) to work through.
Please let me know if you have any feedback or if you find any errors (or feel free to submit a pull request if you're technically savvy)
You may find this reference card a useful reminder for common functions
If you find yourself wanting to cite this course, the easiest way to do so is to cite the Week 1 introductory guide, which is available as a pre-print on the Open Science Framework, and points to the larger course. You can do so as follows:
Murphy, S. C. (2017, May 3). A Psychologist's Guide to R. Retrieved from osf.io/v48zr
If you would prefer to directly cite the repository, you can do so as follows:
Murphy, S. C. (2017, May 3). A Psychologist's Guide To R. Retrieved [Insert Date], from https://github.com/seanchrismurphy/A-Psychologists-Guide-to-R. DOI: 10.5281/zenodo.570953
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
