2.8 Summary: What did we learn so far?

  • Visualization…
    • …allows us to see things that were otherwise invisible (e.g. Hainmueller, Mummolo, and Xu 2016; Imai, Kim, and Wang 2018)
    • … can summarize a lot of information in a comprehensible way (Bauer 2018)
    • …may (should) tell a story (think of Minard’s graph)
    • …may be used to explain things (e.g., Imai, Kim, and Wang 2018)
    • …can be used to persuade others of facts (Figures and Legewie 2019) (see also Forensic architecture = visual detectives)


Bauer, Paul C. 2018. “Unemployment, Trust in Government, and Satisfaction with Democracy: An Empirical Investigation.” Socius 4 (January): 1–14.

Figures, Kalisha Dessources, and Joscha Legewie. 2019. “Visualizing Police Exposure by Race, Gender, and Age in New York City.” Socius 5 (January): 2378023119828913.

Hainmueller, J, J Mummolo, and Y Xu. 2016. “How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice.”

Imai, Kosuke, In Song Kim, and Erik Wang. 2018. “Matching Methods for Causal Inference with Time-Series Cross-Section Data.” Princeton University 1.