Visualization for model building 1
Materials from class on Monday, June 13, 2022
Area-level analysis of Brexit vote
- R. Beecham, N. Williams, and L. Comber, “Regionally-structured explanations behind area-level populism: An update to recent ecological analyses,” PLOS One 15, no. 3 (2020): e0229974.
- R. Beecham, A. Slingsby, and C. Brunsdon, “Locally-varying explanations behind the United Kingdom’s vote to leave the European Union ,” Journal of Spatial Information Science 16 (2018): 117–136.
- R. Harris and M. Charlton, “Voting Out of the European Union: Exploring the Geography of Leave,” Environment and Planning A: Economy and Space 48, no. 11 (2016): 2116–2128.
Graphical inference
- R. Beecham et al., “Map Line-Ups: Effects of Spatial Structure on Graphical Inference,” IEEE Transactions on Visualization & Computer Graphics 23, no. 1 (2017): 391–400.
- H. Wickham et al., “Graphical Inference for Infovis,” IEEE Transactions on Visualization and Computer Graphics (Proc. InfoVis ’10) 16, no. 6 (2010): 973–979.
Model-building in R
- K. Healy, Data Visualization: A Practical Introduction (Princeton: Princeton University Press, 2018).
– Chapter 7
Free online. - H. Wickham and G. Grolemund, R for Data Science: Import, Tidy, Transform, Visualize, and Model Data (Sebastopol, California: O’Reilly Media, 2017).
– Chapters 22, 23, 24, 25
Free online.