Skip to main content

Interactive Data Visualizations for Teaching Civic Statistics

  • Chapter
  • First Online:
Statistics for Empowerment and Social Engagement

Abstract

How might you use data visualisation in your teaching? Here, we offer some ideas, and some provocations to review your teaching. We begin with an invitation to examine some of the historical landmarks in data visualisation (DV), to classify the data presented, and to describe the benefits of a sample of the DV to users. Early uses of DV by Nightingale and Neurath are shown, to provide examples of DV which communicated the need for action, and provoked social change. A number of modern DVs are presented, categorised as: tools to display individual data sets and tools for the exploration of specific rich data sets. We argue that students introduced to the core features of Civic Statistics can acquire skills in all of the facets of Civic Statistics set out in Chap. 3. We conclude by revisiting Herschel, to provoke thoughts about the balance of activities appropriate to statistics courses.

The process by which I propose to accomplish this is one essentially graphical … by bringing in the aid of the eye and hand to guide the judgment, in a case where judgment only, and not calculation, can be of any avail. Herschel (1833, p. 178)

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

eBook
USD 12.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    http://datavis.ca/milestones/

  2. 2.

    http://codex-atlanticus.it/#/

  3. 3.

    http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html

  4. 4.

    https://en.wikipedia.org/wiki/Red_Vienna

  5. 5.

    https://www.youtube.com/watch?v=5tDOcUb4KFk

  6. 6.

    https://realrisk.wintoncentre.uk/

  7. 7.

    https://www.esci.thenewstatistics.com/

  8. 8.

    https://cast.idems.international/

  9. 9.

    https://www.stat.auckland.ac.nz/~wild/iNZight/

  10. 10.

    https://www.gapminder.org/

  11. 11.

    http://www.oecdbetterlifeindex.org/#

  12. 12.

    https://rawgraphs.io/

  13. 13.

    https://www.datawrapper.de/

  14. 14.

    https://www.tableau.com/en-gb

  15. 15.

    https://www.jmp.com/en_us/software/data-analysis-software.html

  16. 16.

    https://developers.google.com/chart/interactive/docs

  17. 17.

    https://codap.concord.org/

  18. 18.

    https://www.tinkerplots.com/

  19. 19.

    https://fathom.concord.org/

  20. 20.

    https://plotly.com/python/

  21. 21.

    https://d3js.org/

  22. 22.

    https://wattenberger.com/blog/d3

  23. 23.

    See https://iase-web.org/islp/pcs/documents/Dynamic-Visualisation-Tools.pdf?1543033028

  24. 24.

    http://www.climate-lab-book.ac.uk/spirals

  25. 25.

    https://www.theguardian.com/environment/2019/jun/07/oceans-demise-the-end-of-the-arctic-as-we-know-it

  26. 26.

    https://www.nature.com/scitable/knowledge/library/milankovitch-cycles-paleoclimatic-change-and-hominin-evolution-68244581/

  27. 27.

    http://flowingdata.com/2015/09/23/years-you-have-left-to-live-probably

  28. 28.

    https://www.ssa.gov/oact/STATS/table4c6.html

  29. 29.

    https://www.ons.gov.uk/visualisations/nesscontent/dvc219/pyramids/index.html

  30. 30.

    https://www.worldlifeexpectancy.com/world-population-pyramid

  31. 31.

    http://www.oecdbetterlifeindex.org/

  32. 32.

    http://archive.wceruw.org/cl1/flag/cat/math/math/math1.htm

  33. 33.

    https://wid.world/world/#shweal_p0p50_z/US;CN/last/eu/k/p/yearly/s/false/-2.4595/20/curve/false/country

  34. 34.

    https://infographics.economist.com/2018/DemocracyIndex/

  35. 35.

    https://sdgs.un.org/

  36. 36.

    https://sustainabledevelopment.un.org/content/unsurvey/index.html

  37. 37.

    https://unstats.un.org/sdgs/indicators/database/

  38. 38.

    http://www.sdgsdashboard.org/

  39. 39.

    https://ec.europa.eu/eurostat/cache/digpub/sdgs/index.html

  40. 40.

    https://sdginterlinkages.iges.jp/visualisationtool.html

  41. 41.

    https://ig.ft.com/coronavirus-chart/

  42. 42.

    https://www.ft.com/content/4743ce96-e4bf-11e7-97e2-916d4fbac0da

  43. 43.

    https://medium.economist.com/mistakes-weve-drawn-a-few-8cdd8a42d368

  44. 44.

    https://www.nytimes.com/column/whats-going-on-in-this-graph

References

  • Balbi, A., & Guerry, A.-M. (1829). Statistique comparé de l'état de l'instruction et du nombre des crimes dans les divers arrondissements des Académies et des Cours Royales de France. Jules Renouard.

    Google Scholar 

  • Cleveland, W. (1985). The elements of graphing data. Wadsworth Advanced Books and Software.

    Google Scholar 

  • Davison, R. (1943). Social security: The story of British social progress and the Beveridge plan. Harrap. Figure 15 reproduced in Neurath (2010).

    Google Scholar 

  • Friendly, M. & Denis, D. J. (2001). Milestones in the history of thematic cartography, statistical graphics, and data visualization.

    Google Scholar 

  • Funkhouser, H. G. (1937). Historical development of the graphical representation of statistical data. Osiris, 3, 269–404. http://www.jstor.org/stable/301591

    Article  MATH  Google Scholar 

  • Harford, T. (2020). How to make the world add up. The Bridge Street Press.

    Google Scholar 

  • Herschel, J. (1833). On the investigation of the orbits of revolving double stars. Memoirs of the Royal Astronomical Society. Priestley and Wea.

    Google Scholar 

  • Lopes, P., Teixeira, S., Campos, P., Ridgway, J., Nicholson, J. (2018) Civic.Stat.Map - Mapping datasets, viz tools, statistical concepts and social themes, In M. A. Sorto, A. White, & L. Guyot (Eds.), Looking back, looking forward. Proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018). International Statistical Institute. iase-web.org [© 2018 ISI/IASE].

  • McCandless, D. (2012). Information is beautiful. Collins.

    Google Scholar 

  • Neurath, O. (2010). From hieroglyphics to isotype. Hyphen Press.

    Google Scholar 

  • Nightingale, F. (1858). Notes on matters affecting the health, efficiency, and hospital administration of the British Army.

    Google Scholar 

  • Piketty, T. (2013). The economics of inequality. Harvard University Press.

    MATH  Google Scholar 

  • Ridgway, J., Swan, M., & Burkhardt, H. (2001). Assessing mathematical thinking via FLAG. In D. Holton & M. Niss (Eds.), Teaching and learning mathematics at university level - An ICMI study (pp. 423–430). Kluwer Academic.

    Chapter  Google Scholar 

  • Ridgway, J., Nicholson, J., Campos, P., & Teixeira, S. (2017). Tools for visualising data: A review. In: A. Molnar (Ed.), Teaching statistics in a data rich world Proceedings of the satellite conference of the International Association for Statistical Education (IASE), July 2017, Rabat. http://iase-web.org/documents/papers/sat2017/IASE2017%20Satellite%20R16_RIDGWAY.pdf

  • Stiglitz, J., Fitousi, J.-P., & Durand, M. (2018). Beyond GDP: Measuring what counts for economic and social performance. OECD. https://www.oecd.org/social/beyond-gdp-9789264307292-en.htm

    Book  Google Scholar 

  • Swan, M., & Ridgway, J. (2001). Assessing mathematical thinking: Field-tested learning assessment guide. National Institute for Science Education, University of Wisconsin-Madison. http://www.wcer.wisc.edu/nise/cl1/flag/

    Google Scholar 

  • Tufte, E. R. (1997). Visual explanations: Images and quantities, evidence and narrative. Graphics Press.

    MATH  Google Scholar 

  • Tufte, E. R. (2006). The visual display of quantitative information. Graphics Press.

    Google Scholar 

  • Tukey, J. W. (1977). Exploratory data Analysis. Pearson.

    MATH  Google Scholar 

  • Wainer, H. (2000). Visual revelations: Graphical tales of fate and deception from Napoleon Bonaparte to Ross Perot. Erlbaum.

    Google Scholar 

  • Wainer, H. (2013). Medical illuminations: Using evidence, visualization and statistical thinking to improve healthcare. Oxford University Press.

    Google Scholar 

  • Watts, J. (2019). The end of the Arctic as we know it. Guardian, 7 June 2019. https://www.theguardian.com/environment/2019/jun/07/oceans-demise-the-end-of-the-arctic-as-we-know-it

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jim Ridgway .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ridgway, J., Campos, P., Nicholson, J., Teixeira, S. (2022). Interactive Data Visualizations for Teaching Civic Statistics. In: Ridgway, J. (eds) Statistics for Empowerment and Social Engagement. Springer, Cham. https://doi.org/10.1007/978-3-031-20748-8_5

Download citation

Publish with us

Policies and ethics