Handling Attention Points: Data, Charts and Graphics

  • Patrick Dunleavy
Part of the Palgrave Study Skills book series (MASTSK)


When readers first scan your text they will pay disproportionate attention to any organizers and summaries they encounter, but also to visually distinctive ‘attention points’ which stand out from the main text — especially tables, charts, diagrams, maps, photographs and text boxes. At this ‘eye-balling’ stage readers will often try to make sense of each attention point on its own, without reading closely the accompanying text, since they are trying to decide whether to focus down for serious study, and where. If data presentation is important to your thesis, or other elements play a key role in the exposition (for instance, diagrams in a theoretical argument or photographs in project work), then how you handle attention points will strongly influence readers’ views of the professionalism of your approach. Even if attention points are few and far between in your text, PhD examiners and subsequent readers (such as journal editors and reviewers) will expect them to be competently delivered. Later, too, you will go to conferences, and have only 15 or 20 minutes to give an oral presentation, or possibly secure only a poster session in a crowded conference venue. On these occasions people focus a lot of attention on your presentation slides or other exhibits. Usually these slides will either be versions of your existing attention points or designed on similar principles.


Cataract Operation Main Text Decimal Point Health Board Attention Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    National Audit Office, Presenting Data in Reports (London: National Audit Office, 1998), p. 1.Google Scholar
  2. 3.
    Quoted in L. D. Eigen and J. P. Siegel, Dictionary of Political Quotations (London: Robert Hale, 1994), p. 470.Google Scholar
  3. 4.
    National Audit Office, Presenting Data in Reports (London: NAO, 1999), p. 10.Google Scholar
  4. 5.
    See A. S. C. Ehrenberg, A Primer in Data Reduction (Chichester: Wiley, 1982), for a full set of examples).Google Scholar
  5. 7.
    My favourite sources are now dated but still useful works, such as Catherine Marsh, Exploring Data: An Introduction to Data Analysis for Social Scientists (Cambridge: Polity, 1988); Ehrenberg, A Primer in Data Reduction;Google Scholar
  6. B. H. Erickson and T. A. Nozanchuk, Understanding Data: An Introduction to Exploratory and Confirmatory Data Analysis for Students in the Social Sciences (Milton Keynes: Open University Press, 1979);Google Scholar
  7. John W. Tukey, Exploratory Data Analysis (Reading, MA: Addison-Wesley, 1977);Google Scholar
  8. Frederick Mosteller and John W. Tukey, Data Analysis and Regression: A Second Course in Statistics (Reading, MA: Addison-Wesley, 1977).Google Scholar
  9. 9.
    Umberto Eco, Kant and the Platypus: Essays on Language and Cognition (London: Verso, 1997), translated by Alastair McEwan, p. 83.Google Scholar

Copyright information

© Patrick Dunleavy 2003

Authors and Affiliations

  • Patrick Dunleavy
    • 1
  1. 1.London School of Economics and Political ScienceLondonUK

Personalised recommendations