2.8 Resources

This section contains links to general resources on visualization and to the ggplot2 package.

References

Anscombe, F. J. (1973). Graphs in statistical analysis. The American Statistician, 27(1), 17–21. https://doi.org/10.2307/2682899
Bertin, J. (2011). Semiology of graphics: Diagrams, networks, maps (Vol. 1). ESRI Press.
Cairo, A. (2012). The functional art: An introduction to information graphics and visualization. Berkeley CA: New Riders.
Cairo, A. (2016). The truthful art: Data, charts, and maps for communication. Berkeley CA: New Riders.
Chang, W. (2012). R graphics cookbook: Practical recipes for visualizing data (2nd ed.). Retrieved from https://r-graphics.org/
Cleveland, W. S., & McGill, R. (1985). Graphical perception and graphical methods for analyzing scientific data. Science, 229(4716), 828–833. https://doi.org/10.1126/science.229.4716.828
Gillespie, C., Locke, S., Davies, R., & D’Agostino McGowan, L. (2024). datasauRus: Datasets from the datasaurus dozen. Retrieved from https://github.com/jumpingrivers/datasauRus
Healy, K. (2018). Data visualization: A practical introduction. Retrieved from https://socviz.co/
Kabacoff, R. (2018). Data visualization with R. Retrieved from https://rkabacoff.github.io/datavis/
Matejka, J., & Fitzmaurice, G. (2017). Same stats, different graphs: Generating datasets with varied appearance and identical statistics through simulated annealing. Proceedings of the 2017 CHI conference on human factors in computing systems, 1290–1294. https://doi.org/10.1145/3025453.3025912
Neth, H. (2023a). Data science for psychologists. Retrieved from https://bookdown.org/hneth/i2ds/
R Core Team. (2024). R base: A language and environment for statistical computing. Retrieved from https://www.R-project.org
Tufte, E. R. (2001). The visual display of quantitative information (2nd ed.). Cheshire, CT: Graphics Press.
Tufte, E. R. (2006). Beautiful evidence (Vol. 1). Cheshire, CT: Graphics Press.
Tufte, E. R., Goeler, N. H., & Benson, R. (1990). Envisioning information (Vol. 126). Cheshire, CT: Graphics Press.
Wickham, H. (2016). ggplot2: Elegant graphics for data analysis (2nd ed.). Retrieved from https://ggplot2-book.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., Çetinkaya-Rundel, M., & Grolemund, G. (2023). R for data science (2nd ed.). Retrieved from https://r4ds.hadley.nz
Wickham, H., Chang, W., Henry, L., Pedersen, T. L., Takahashi, K., Wilke, C., … van den Brand, T. (2024). ggplot2: Create elegant data visualisations using the grammar of graphics. Retrieved from https://ggplot2.tidyverse.org
Wickham, H., & Grolemund, G. (2017). R for data science: Import, tidy, transform, visualize, and model data. Retrieved from http://r4ds.had.co.nz
Wilke, C. O. (2019). Fundamentals of data visualization: A primer on making informative and compelling figures. Retrieved from https://clauswilke.com/dataviz/
Wilkinson, L. (2005). The grammar of graphics (2nd edition). Springer.
Yau, N. (2011). Visualize this: The FlowingData guide to design, visualization, and statistics. Hoboken, NJ: John Wiley & Sons.
Yau, N. (2013). Data points: Visualization that means something. Hoboken, NJ: John Wiley & Sons.