Hardcover New The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the ...worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.Read moreShow Less
The Visual Display of Quantitative Information contains 250 illustrations of the best (and a few of the worst) statistical charts, graphics, and tables, with a detailed analysis of how to display quantitative data for precise, quick, effective analysis. Highest quality book design and production throughout.
Celebrated designer and educator Edward R. Tufte here shares the fundamentals of graphic design in a book that has come to be considered a classic. Scientific American described this seminal work as "original, beautifully presented, sharp and learned...a work of art."
A classic reference. The overall intention and power of the book is stunning.
This beautifully typeset, illustrated, and printed large-format volume is an accurate, funny, and downright rude short course in the history and practice of statistical graphics. A touchstone of style.
Original, beautifully presented, sharp and learned, this book is a work of art. The art here is cognitive art, the graphic display of relations and empirical data, now an indispensable tool of science and engineering.
Edward Tufte is a professor at Yale University, where he teaches courses in statistical evidence and information design. His books include Visual Explanations, Envisioning Information, The Visual Display of Quantitative Information, Political Control of the Economy, Data Analysis for Politics and Policy, and Size and Democracy (with Robert A. Dahl).
He is a fellow of the American Statistical Association, the American Academy of Arts and Sciences, the Guggenheim Foundation, and the Center for Advanced Study in the Behavioral Sciences. He has received honorary doctorates from The Cooper Union and Connecticut College, the Phi Beta Kappa Award in Science, and the Joseph T. Rigo Award for contributions to software documentation from the Association for Computing Machinery.
Chapter 3: Sources of Graphical Integrity and Sophistication
Why do artists draw graphics that lie? Why do the world's major newspapers and magazines publish them?
Although bias and stereotyping are the origin of more than a few graphical distortions, the primary causes of inept graphical work are to be found in the skills, attitudes, and organizational structure prevailing among those who design and edit statistical graphics.
Lack of Quantitative Skills of Professional Artists
Lurking behind the inept graphic is a lack of judgment about quan-titative evidence. Nearly all those who produce graphics for masspublication are trained exclusively in the fine arts and have hadlittle experience with the analysis of data. Such experience is essen-tial for achieving precision and grace in the presence of statistics,but even textbooks of graphical design are silent on how to thinkabout numbers. Illustrators too often see their work as an exclu-sively artistic enterprise-the words "creative," "concept," and"style" combine regularly in all possible permutations, a Big Thinkjargon for the small task of constructing a time-series a few datapoints long. Those who get ahead are those who beautify data,never mind statistical integrity.
The Doctrine That Statistical Data Are Boring
Inept graphics also flourish because many graphic artists believe that statistics are boring and tedious. It then follows that decorated graphics must pep up, animate, and all too often exaggerate what evidence there is in the data. For example:
Time's first full-time chart specialist, an art-school graduate, says that in his work, "The challenge is to present statistics as avisual idea rather than a tedious parade of numbers."
The opening sentence of the chapter on statistical charts in Jan White's Graphic Idea Notebook: "Why are statistics so boring?" Sample illustrations supposedly reveal "Dry statistics turned into symbolic graphics" and "Plain statistics embellished or humanized with pictures."
A fine book on graphics, Herdeg's Graphis/Diagrams, is described by its publisher: "An international review demonstrating convincingly that statistical and diagrammatic graphics do not necessarily have to be dull."
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 skillstatistical skill-and hard work as creating a beautiful design or covering a complex news story.
The Doctrine That Graphics Are Only for the Unsophisticated Reader
Many believe that graphical displays should divert and entertain those in the audience who find the words in the text too difficult. For example:
Consumer Reports describes the design of their new consumer magazine for children: "For the first test issue, CU's professional staff produced an article about sugar that was longer on graphics than on information. We had feared children might be overwhelmed by too many facts."
An art director with overall responsibility for the design of some 3,ooo data graphics each year (yielding 2.5 billion printed images) said that graphics are intended more to lure the reader's attention away from the advertising than to explain the news in any detail. "Unlike the advertisements," he said, "at least we don't put naked women in our graphics...
Data graphics visually display measured quantities by means of the combined use of points, lines, a coordinate system, numbers, symbols, words, shading, and color.
The use of abstract, non-representational pictures to show numbers is a surprisingly recent invention, perhaps because of the diversity of skills required-the visual-artistic, empirical-statistical, and mathematical. It was not until 1750-1800 that statistical graphicslength and area to show quantity, time-series, scatterplots, and multivariate displays-were invented, long after such triumphs of mathematical ingenuity as logarithms, Cartesian coordinates, the calculus, and the basics of probability theory. 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."
Modern data graphics can do much more than simply substitute for small statistical tables. At their best, graphics are instruments for reasoning about quantitative information. Often the most effective way to describe, explore, and summarize a set of numberseven 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.
The first part of this book reviews the graphical practice of the two centuries since Playfair. The reader will, I hope, rejoice in the graphical glories shown in Chapter 1 and then condemn the lapses and lost opportunities exhibited in Chapter 2. Chapter 3, on graphical integrity andsophistication, seeks to account for these differences in quality of graphical design.
The second part of the book provides a language for discussing graphics and a practical theory of data graphics. Applying to most visual displays of quantitative information, the theory leads to changes and improvements in design, suggests why some graphics might be better than others, and generates new types of graphics. 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.
This is a book about the design of statistical graphics and, as such, it is concerned both with design and with statistics. But it is also about how to communicate information through the simultaneous presentation of words, numbers, and pictures. The design of statistical graphics is a universal matter-like mathematics-and is not tied to the unique features of a particular language. The descriptive concepts (a vocabulary for graphics) and the principles advanced apply to most designs. I have at times provided evidence about the scope of these ideas, by showing how frequently a principle applies to (a random sample of) news and scientific graphics.
Each year, the world over, somewhere between goo billion (9 X 10 and 2 trillion (2 X 1012) images of statistical graphics are printed. The principles of this book apply to most of those graphics. Some of the suggested changes are small, but others are substantial, with consequences for hundreds of billions of printed pages.
But I hope also that the book has consequences for the viewers and makers of those images-that they will never view or create statistical graphics the same way again. That is in part because we are about to see, collected here, so many wonderful drawings, those of Playfair, of Minard, of Marey, and, nowadays, of the computer.
Most of all, then, this book is a celebration of data graphics.
A Classic: if you need to graph data, here is help.
This is his first in what has become a series. With numerous examples of good practice and also of delightfully bad practice, he shows how to help the viewer see the data, not the graphic process, presuming of course that the purpose is honest communication not misdirection. Better graphs show more data (thus: 'maximise data ink') but without shouting about themselves (thus: 'avoid cybercrud and The Duck') so that subtle patterns may be perceived more readily. And some patterns are not at all subtle: one gazes at his reproduction of the graph depicting Napoleon's attack on Russia, and the vast horror of the retreat is evident. The purpose of a Visual Display is to seek understanding, and he shows techniques that will support this search, while puncturing the illusions of those whose efforts had other objectives.
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