Appendix A — Additional Resources

If you would like additional practice, you can check out the other UofG PsyTeachR course books.

Level 1 - Intro to R (overlaps with Msc Conv book), data wrangling, data viz, descriptive statistics
Level 2 - Our second-year undergraduate course introduces statistical concepts such as permutation tests,t-tests, NHST, alpha, power, effect size, and sample size. Semester 2 focusses on correlations and the general linear model.
Level 3: This third-year undergraduate course teaches students how to specify, estimate, and interpret statistical models corresponding to various study designs, using a General Linear Models approach.
MSc Data Skills: This course provides an overview of skills needed for reproducible research and open science using the statistical programming language R. Students will learn about data visualisation, data tidying and wrangling, archiving, iteration and functions, probability and data simulations, general linear models, and reproducible workflows.

We also highly recommend the following, they will help practice your data wrangling skills but also they’re great options if you’re enjoying R and want to stretch yourself:

Open Stats Lab - this wonderful resource gives you practice at running statistical tests by providing you with datasets from published papers.
R for Data Science - written by the authors of the tidyverse, this is a great resource for additional data wrangling practice and more depth on many of the tidyverse functions.
Text Mining with R - Shows you how to use R to work with text. This isn’t something we cover in this course, but it uses the same data wrangling skills and be a very useful additional skill to have.
How to make BBC style graphics - Ever wondered how the BBC News makes their data visualisation? Well, now you can make your own!
Data Vizualisation - this is an entire book on data visualisation and goes into detail on how to take ggplot to its limits.