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The Visual Display of Quantitative Information, 2nd edition

The Visual Display of Quantitative Information, 2nd editionAuthor: Edward R. Tufte
Publisher: Graphics Press

List Price: $40.00
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New (30) Used (38) Collectible (7) from $17.59

Seller: CyrustheGreat
Rating: 4.5 out of 5 stars 110 reviews
Sales Rank: 1043

Media: Hardcover
Edition: 2
Pages: 197
Number Of Items: 1
Shipping Weight (lbs): 2.1
Dimensions (in): 10.7 x 8.9 x 0.9

ISBN: 0961392142
Dewey Decimal Number: 001.4226
EAN: 9780961392147
ASIN: 0961392142

Publication Date: May 2001
Availability: Usually ships in 1-2 business days

Features:
  • ISBN13: 9780961392147
  • Condition: USED - VERY GOOD
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Editorial Reviews:

Amazon.com Review
A timeless classic in how complex information should be presented graphically. The Strunk & White of visual design. Should occupy a place of honor--within arm's reach--of everyone attempting to understand or depict numerical data graphically. The design of the book is an exemplar of the principles it espouses: elegant typography and layout, and seamless integration of lucid text and perfectly chosen graphical examples. Very Highly Recommended.

Product Description
A modern classic. Tufte teaches the fundamentals of graphics, charts, maps and tables. "A visual Strunk and White" (The Boston Globe). Includes 250 delightfullly entertaining illustrations, all beautifully printed.


Customer Reviews:
Showing reviews 1-5 of 110
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5 out of 5 stars Data decorators, data-ink, instant chartjunk, and naked women   November 14, 2009
Abhinav Agarwal (Bangalore, India)
Perhaps the single most accessible book on data visualizations. You are given a tour of the history of visualizations, the seminal contributions of people such as Playfair, Tukey, and others, a rogues' gallery of sorts of awful visualizations, a peek into small-multiples visualizations, and an exposition of the principles of good graphic design and visualizations. A must-have book for anyone interested in good data visualizations.

Tufte's contention is that a lack of adequate knowledge and expertise and a mistaken notion about numbers are to blame for bad visualizations. The principles of good visualizations, on the other hand, are few and simple. The book is all about exposing bad examples and enunciating these good principles, beautifully illustrated with examples, and printed on excellent quality paper.

Suggested Reading:
-----------------
Supplement this excellent book with at least the following, if you are interested in digging deeper into the area of data visualizations:
- Information Visualization, Second Edition: Perception for Design (Interactive Technologies)
- Information Dashboard Design: The Effective Visual Communication of Data


The rest of the review can be best told, in my opinion, through quotes from the book:
---------------------------------------------------------
"The theory of the visual display of quantitative information consists of principles that generate design options... The principles should not be applied rigidly or in a peevish spirit... 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." [page 191]

While seemingly a trivial matter, the issue of the size of charts, whether they should be tall or horizontal, Tufte states that "Graphics should tend toward the horizontal, greater in length than height..." and "Many graphics plot, in essence (cause and effect) and a longer horizontal helps to elaborate the workings of the causal variable in more detail." [pages 186, 187]

Time-series displays are at their best for big data sets with real variability. [page 30]

Chapter 2, "Graphical Identity" Is a stunning collection of graphs that distort, lie, deceive, and exhibit all manners of skills other than those required for data visualizations.
"Much of twentieth-century thinking about statistical graphics has been preoccupied with the question of how some amateurish chart might fool the naive viewer. ... At the core of the preoccupation with deceptive graphics was the assumption that data graphics were mainly devices for showing the obvious to the ignorant. ... The assumption led down two fruitless paths in the graphically barren years from 1930 to 1970: First, that graphics had to be "alive", "communicatively dynamic," overdecorated and exaggerated.. Second, that the main task of graphical analysis was to detect and denounce deception." [page 53]

"A graphic does not distort if the visual representation of the data is consistent with the numerical representation." [page 55]
Which leads to his definition of the term, "Lie Factor", which he defines as the "size of the effect shown in graphic" divided by "size of effect in chart".

"Another way to confuse data variation with design variation is to use areas to show one-dimensional data" [page 69]
An example cited is the depiction of "the rate of inflation", for which, "graphs show currency shrinking on two dimensions, even though the value of money is one-dimensional." [page 70]

A very important observation quoted in Chapter 3 comes from Howard Weiner - "Perhaps the reason is an increase in the perceived need for graphs ... without a concomitant increase in training in their construction." [page 79]
Tufte elaborates: "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. ..." "... 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." [page 79]
And "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. ... as the art bureaucracy grows, style replaces content. And the word people, having lost space in the publication to data decorators, console themselves... " [page 80]

Tufte defines "data-ink" in Ch 4 ("Theory of Data Graphics") as "the non-erasable core of a graphic, the non-redundant ink arranged in response to variations in the numbers represented
Data-ink ration = data-ink / total ink used to print the graphic" [page 93]
So, it should not come as a surprise, when Tufte takes a single bar with a value label at the top of the bar, and states that "the labeled, shaded bar of the bar chart, for example, unambiguously locates the altitude in size separate ways." [page 96].

Chapter 5 - "Charkjunk: Vibrations, Grids, and Ducks" is perhaps the most humorous chapter, as the title itself suggests. A quote from Johnathan Swift, indicting 17th-century cartographers, says it all - "With save pictures fill their gaps, And o'er unhabitable downs, Place elephants for want of towns." [page ] ouch!

"This may well be the worst graphic ever to find its way into print:" [page 118] refers to a "series of weird three-dimensional displays appearing in the magazine American Education in the 1970s (that) delighted connoisseurs of the graphically preposterous. Here five colors report, almost by happenstance, only five pieces of data..." [page 118]

You may not, and I certainly did not agree with Tufte's suggestions for maximizing the data-ink efficiency of the box-plot, in the chapter on "Data-ink Maximization", but they are worth examining nonetheless. However, his redesign of the bar chart, with a border and other accouterments, on pages 126-128, are excellent.

Many examples of bad visualizations cited in the book are from the "New York Times", so it is sort of reassuring when you see that the quality of visualizations on the NYT has improved a lot, and are frequently the objects of animated discussions. There may be hope, after all.

The review title, explained, at least part thereof:
--------------------------------------------------
And what about that slightly inappropriate word in the title of the review?
Tufte writes that an art director with overall responsibility for the design of over 3,000 graphics annually had this to say - "graphics are intended to 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.' " [page 80] We must be all thankful for small mercies, I suppose.



5 out of 5 stars Perfect condition   November 1, 2009
Rasheed Wright
0 out of 1 found this review helpful

The book was in the exact condition the seller described. Fast shipment excellent seller!!!


5 out of 5 stars A must!   October 25, 2009
Lionel (France)
See the world through the eyes of someone who has seen it before... and discover how much time you can save!


4 out of 5 stars Readable reference   October 18, 2009
Andrew K. Klein (Ohio)
Very good book about how to display statistics in charts and graphs. I wish there had been more examples of what makes a good graph, but overall it's a great reference for anyone who's looking to make a chart or graph.


5 out of 5 stars The negative review make no sense to me   September 15, 2009
ChemSciGuy (Midland, MI USA)
4 out of 4 found this review helpful

I am a working scientist. As such, I make my living conveying information to others. Tufte's books are all great, but this one is the most important and is a must read for ANYONE whose business involves the use of numerical data.

Tufte does a great job of stressing making graphics that tell the story efficiently and clearly. Display of quantitative data is all about making data accessible to the audience. Graphs are used because they make the data come alive in ways that tables simply cannot. When we are successful, our audience relates to plotted data and is drawn to the conclusions we have drawn. Creativity in reaching the audience is possible with both quill pen and computer.

Those critics who criticize the book as lacking state-of-the-art computer graphics have really missed the point. Tufte is agnostic to the tools used to craft the message. What he shows is that effective graphics resonate with an audience, they don't confuse it. That message transcends any particular technology. This isn't a book on how to use Excel to make plots, it is about the thought process required to make the plots better whether using Excel or graph paper.


Showing reviews 1-5 of 110
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