The psyTeachR team at the University of Glasgow School of Psychology and Institute of Neuroscience and Psychology has successfully made the transition to teaching reproducible research using R across all undergraduate and postgraduate levels. Our curriculum now emphasizes essential ‘data science’ graduate skills that have been overlooked in traditional approaches to teaching, including programming skills, data visualisation, data wrangling and reproducible reports. Students learn about probability and inference through data simulation as well as by working with real datasets.

This website contains our open materials for teaching reproducible research.

Course Books

Undergraduate Series

Level 1: Data Skills

Our first-year undergraduate course covers current state of psychological science and what Open Science is as well as its importance. It also aims to make students confident and competent at using RStudio as a tool to achieve good data management skills.

Authors: Emily Nordmann, Heather Cleland-Woods
Contact: Emily Nordmann
Contributors: Jack Taylor, Shannon McNee

Level 2: Analysis

Our second-year undergraduate course covers data skills such as R Markdown, data wrangling with tidyverse, and data visualisation with ggplot2. It also introduces statistical concepts such as permutation tests, NHST, alpha, power, effect size, and sample size. Semester 2 focusses on correlations and the general linear model.

Authors: Phil McAleer, Carolina Kuepper-Tetzel, Helena Paterson
Contact: Carolina Kuepper-Tetzel

Level 3: Statistical Models

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.

Author: Dale Barr

Postgraduate Books

Fundamentals of Quantitative Analysis

This book contains materials for students on the MSc Conversion in Psychological Studies/Science, a one-year postgraduate degree for students with a non-psychology undergraduate degree. This research methods course covers core data skills that allow you to manipulate and analyse quantitative data.

Author: Emily Nordmann
Contact: Phil McAleer

Data Skills for Reproducible Research

This book provides an overview of skills needed for reproducible research and open science using the statistical programming language R and tidyverse packages. It covers data visualisation, data tidying and wrangling, archiving, iteration and functions, probability and data simulations, general linear models, and reproducible workflows. It assumes at least an undergraduate level of methods training, but no prior experience in R.

Authors: Lisa DeBruine, Dale Barr
Contact: Lisa DeBruine
Contributors: Rebecca Lai

Other Books

Glossary of Terms

PsyTeachR books (and external websites) can link to the glossary to define common terms. Anyone can contribute to the glossary through the github project.

Contact: Lisa DeBruine

Data Visualisation Using R, For Researchers Who Don’t Use R

In this tutorial, we provide a practical introduction to data visualisation using R, specifically aimed at researchers who have little to no prior experience of using R.

Authors: Emily Nordmann, Phil McAleer, Wilhelmiina Toivo, Helena Paterson, Lisa DeBruine

Contact: Emily Nordmann