Data Science for Psychologists
Version of 07 July 2020
This book provides an introduction to data science that is tailored to the needs of psychologists, but is also suitable for students of the humanities and other biological or social sciences. This audience typically has some knowledge of statistics, but rarely an idea how data is prepared and shaped to allow for statistical testing. By using various data types and working with many examples, we teach tools for transforming, summarizing, and visualizing data. By keeping our eyes open for the perils of misleading representations, the book fosters fundamental skills of data literacy and cultivates reproducible research practices that enable and precede any practical use of statistics.
The materials in this book are based on a course at the University of Konstanz in 2020. The course provides an introduction to data science in R (R Core Team, 2020) from a tidyverse (Wickham, Averick, et al., 2019) perspective and previously relied on R for Data Science (Wickham & Grolemund, 2017) as its textbook. Both this book and course are supported by the R package ds4psy (Neth, 2020), which provides datasets and functions used in examples and exercises.
Neth, H. (2020). ds4psy: Data science for psychologists. Retrieved from https://CRAN.R-project.org/package=ds4psy
R Core Team. (2020). R: A language and environment for statistical computing. Retrieved from https://www.R-project.org
Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L. D., François, R., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43), 1686. https://doi.org/10.21105/joss.01686
Wickham, H., & Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. Retrieved from http://r4ds.had.co.nz