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The Visual Display Of Quantitative Information by Edward R. Tufte

03 October, 2022 - 11 min read


I. Brief Summary

Edward Tufte was a professor of statistics, graphic design, and political economy at Yale University. He has been described by The New York Times as "the Leonardo da Vinci of Data". He is an expert in the presentation of informational graphics such as charts and diagrams, and is a fellow of the American Statistical Association. His idea of data-ink ratio is a great analytical tool in understanding the true information of a graph versus being a novelty visualization. In a world where visualizations are ordinary, graphical integrity is constantly being breached to get the story out at scale with facts being secondary. He provides many examples of both poor and great display of visual evidence, visual reasoning and visual understanding of quantitative information.

II. Big Ideas

  • Data graphics visually display measured quantities by means of 1the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, and color. The diversity of skills required to build a graph — the visual-artistic, empirical-statistical, and mathematical.
  • It was not until 1750-1800 that statistical graphics, length and area to show quantity, time-series, scatter-plots, and multivariate displays were invented. The remarkable William Playfair (1759-1823) developed or improved upon nearly all the fundamental graphical designs, seeking to replace conventional tables of numbers with the systematic visual representations of his linear arithmetic.
  • Often the most effective way to describe, explore, and summarize a set of numbers even a very large set is to look at pictures of those numbers. Furthermore, of all methods for analyzing and communicating statistical information, well-designed data graphics are usually the simplest and at the same time the most powerful.
  • EXCELLENCE in statistical graphics consists of complex ideas communicated with clarity, precision, and efficiency. Graphical displays should:

    • show the data
    • induce the viewer to think about the substance rather than about methodology, graphic design, the technology of graphic production, or something else
    • avoid distorting what the data have to say
    • present many numbers in a small space
    • make large data sets coherent
    • encourage the eye to compare different pieces of data
    • reveal the data at several levels of detail, from a broad overview to the fine structure
    • serve a reasonably clear purpose: description, exploration, tabulation, or decoration
    • be closely integrated with the statistical and verbal descriptions of a data set.
  • The problem with time-series is that the simple passage of time is not a good explanatory variable: descriptive chronology is not causal explanation. There are occasional exceptions, especially when there is a clear mechanism that drives the Y-variable.
  • Principles of Graphical Excellence:

    • Graphical excellence is the well-designed presentation of interesting data a matter of substance, of statistics, and of design.
    • Graphical excellence consists of complex ideas communicated with clarity, precision, and efficiency.
    • Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.
    • Graphical excellence is nearly always multivariate.
    • Graphical excellence requires telling the truth about the data.
  • Tables usually outperform graphics in reporting on small data sets of 20 numbers or less.
  • Graphical integrity is more likely to result if these six principles are followed:

    • The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented.
    • Clear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity. Write out explanations of the data on the graphic itself. Label important events in the data.
    • Show data variation, not design variation.
    • In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.
    • The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data.
    • Graphics must not quote data out of context.
  • Japanese graphical distinction is consistent with that country's heavy use of statistical techniques in the workplace and extensive quantitative training, even in the early years of school...The five U.S. publications examined rank toward the bottom of the world list...the complete dominance of non-relational designs at the lower-ranked newspapers and magazines. This is unfortunate because the relational graphic, unlike the simpler designs, is an explanatory graphic- surely a natural for news reporting and analysis.
  • The conditions under which many data graphics are produced- the lack of substantive and quantitative skills of the illustrators, dislike of quantitative evidence, and contempt for the intelligence of the audience- guarantee graphic mediocrity. These conditions engender graphics that

    • lie
    • employ only the simplest designs, often unstandardized time-series based on a small handful of data points
    • miss the real news actually in the data.
  • How can graphic mediocrity be remedied? These doctrines blame the victims (the audience and the data rather than the perpetrators. Graphical competence demands three quite different skills: the substantive, statistical, and artistic. Yet now most graphical work, particularly at news publications, is under the direction of but a single expertise--the artistic. Allowing artist-illustrators to control the design and content of statistical graphics is almost like allowing typographers to control the content, style, and editing of prose.
  • Five principles in the theory of data graphics produce substantial changes in graphical design. The principles apply to many graphics and yield a series of design options through cycles of graphical revision and editing:

    • Above all else, show the data.
    • Maximize the data-ink ratio.
    • Erase non-data ink.
    • Erase redundant data-ink.
    • Revise and edit.
  • Chartjunk does not achieve the goals of its propagators. Graphics do not become attractive and interesting through the addition of ornamental hatching and false perspective to a few bars. Chartjunk can turn bores into disasters, but it can never rescue a thin data set. Forgo chartjunk, including moire vibration, the grid (use gray grids), and the duck.
  • Mobilize every graphical element, perhaps several times over, to show the data.
  • Small multiples reflect much of the theory of data graphics:

    • for non-data-ink, less is more
    • for data-ink, less is a bore
  • Aesthetics and Technique in Data Graphics Design

    • Graphical elegance is often found in the simplicity of design and complexity of data
    • Attractive displays of statistical information:

      • have a properly chosen format and design
      • use words, numbers, and drawings together
      • reflect a balance, a proportion, a sense of relevant scale
      • display an accessible complexity of detail
      • often have a narrative quality, a story to tell about the data
      • are drawn in a professional manner, with the technical details of production done with care
      • avoid content-free decoration, including chartjunk
  • Epilogue: Design is choice. The theory of the visual display of quantitative information consists of principles that generate design options and that guide choices among options. The principles should not be applied rigidly or in a peevish spirit; they are not logically or mathematically certain; and it is better to violate any principle than to place graceless or inelegant marks on paper. Most principles of design should be greeted with some skepticism, for word authority can dominate our vision, and we may come to see only through the lenses of word authority rather than with our own eyes. What is to be sought in designs for the display of information is the clear portrayal of complexity. Not the complication of the simple; rather the task of the designer is to give visual access to the subtle and the difficult – that is, the revelation of the complex.

III. Quotes

  • Above all else show the data.
  • Graphics reveal data.
  • Of course, statistical graphics, just like statistical calculations, are only as good as what goes into them.
  • A silly theory means silly graphic.
  • Graphical excellence begins with telling the truth about the data.
  • Graphical excellence is that which gives to the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.
  • Allowing artist-illustrators to control the design and content of statistical graphics is almost like allowing typographers to control the content, style, and editing of prose.
  • The emphasis is on maximizing principles, empirical measures of graphical performance, and the sequential improvement of graphics through revision and editing. Insights into graphical design are to be gained, I believe, from theories of what makes for excellence in art, architecture, and prose.
  • Most of all, then, this book is a celebration of data graphics.
  • Get it right or let it alone. The conclusion you jump to may be your own. — James Thunder
  • As to the propriety and justness of representing sums of money, and time, by parts of space, tho' very readily agreed to by most men, yet a few seem to apprehend that there may possibly be some deception in it, of which they are not aware. — William Playfair, The Commercial and Political Atlas (London, 1786)
  • Different people see the same areas somewhat differently; perceptions change with experience; and perceptions are context-different.
  • Misperception and miscommunication are certainly not special to statistical graphics.
  • Why do artists draw graphics that lie? Why do the world's major newspaper and magazines publish them?...Lurking behind the inept graphic is a lack of judgment about quantitative evidence, Nearly all those who produce graphics for mass publication are trained exclusively in the fine arts and have had little experience with the analysis of data. Such experience is essential for achieving precision and grace in the presence of statistics, but even textbooks of graphical design are silent on how to think about numbers. Illustrators too often see their work as an exclusively artistic enterprise--the words "creative," "concept," and "style" combine regularly in all possible permutations, a Big Think jargon for the small task of constructing a time-series a few data points long. Those who get ahead are those who beautify data, never mind statistical integrity.
  • The doctrine of boring data serves political ends, helping to advance certain interests over others in bureaucratic struggles for control of a publication's resources. For if the numbers are dull dull dull, then an artist, indeed many artists, indeed an Art Department and an Art Director are required to animate the data, lest the eyes of the audience glaze over. Thus the doctrine encourages placing data graphics under control of artists rather than in the hands of those who write the words and know the substance. As the art bureaucracy grows, style replaces content. And the word people, having lost space in the publication to data decorators, console themselves with thoughts that statistics are really rather tedious anyway.
  • If the statistics are boring, then you've got the wrong numbers. Finding the right numbers requires as much specialized skill- statistical skill-and hard work as creating a beautiful design or covering a complex news story.
  • Many believe that graphical displays should divert and entertain those in the audience who find the words in the text too difficult.
  • If you have to explain it, don't use it.
  • ... no nation ranks higher in its collective passion for statistics. In Japan, statistics are the subject of a holiday, local and national conventions, awards ceremonies and nationwide statistical collection and graph-drawing contests. "This year," said Yoshiharu Takahashi, a Government statistician, "we had almost 30,000 entries. Actually, we had 29,836." Entries in the [children's statistical graph contest were screened three times by judges, who gave first prize this year to the work of five 7-year-olds. Their graph creation, titled "Mom, play with us more often," was the result of a survey of 32 classmates on the frequency that mothers play with their offspring and the reasons given for not doing so.... Other children's work examined the frequency of family phone usage and correlated the day's temperature with cicada singing.' — Andrew H. Malcolm
  • It wastes the tremendous communicative power of graphics to use them merely to decorate a few numbers.
  • Like weeds, many varieties of chartjunk flourish.
  • Painting is special, separate, a matter of meditation and contemplation, for me, no physical action or social sport. As much consciousness as possible. Clarity, completeness, quintessence, quiet. No noise, no schmutz, no schmerz, no fauve schwärmerei. Perfection, passiveness, consonance, consummateness. No palpitations, no gesticulation, no grotesquerie. Spirituality, serenity, absoluteness, coherence. No automatism, no accident, no anxiety, no catharsis, no chance. Detachment, disinterestedness, thoughtfulness, transcendence. No humbugging, no button-holing, no exploitation, no mixing things up. — Ad Reinhardt, statement for the catalogue of the exhibition, "The New Decade: 35 American Painters and Sculptors," Whitney Museum of American Art, New York, 1955.
  • Graphical elegance is often found in simplicity of design and complexity of data.