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The Visual Display of Quantitative Information Hardcover – May 1, 2001

ISBN-13: 858-0001045689 ISBN-10: 0961392142 Edition: 2nd

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Product Details

  • Hardcover: 200 pages
  • Publisher: Graphics Pr; 2nd edition (May 2001)
  • Language: English
  • ISBN-10: 0961392142
  • ISBN-13: 978-0961392147
  • Product Dimensions: 1 x 9 x 11 inches
  • Shipping Weight: 2.2 pounds (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (186 customer reviews)
  • Amazon Best Sellers Rank: #1,713 in Books (See Top 100 in Books)

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Customer Reviews

Buy this book and you will have a very tough time putting it down.
Aneil K. Mishra
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.
ChemSciGuy
The book outlines Tufte's theories for better displaying data in graphical forms.
W. Sean McLaughlin

Most Helpful Customer Reviews

259 of 264 people found the following review helpful By Durand Sinclair on February 7, 2000
Format: Hardcover
You know what's so good about this book? The research, that's what. In showing both good and bad graphic design, Tufte has examples from as far back as 1686, and many examples from the 18th,19th & 20th centuries and from many different countries.
Good graphic design, he argues, reveals the greatest number of ideas in the shortest time with the least ink in the smallest space. Interestingly, some of the best examples of this come from the pre-computer era, when graphics had to be drawn by hand (and therefore more thought had to go into their design, rather than the author just calling up the Bar Graph template on the desktop.) For example, that picture you can see on the front cover of the book is actually a train timetable that packs a whole list of arrivals and departures at many different stations into a single little picture. A better example (and the "best statistical graphic ever drawn") shows Napoleon's route through Europe. It shows a) the map b) where he went c) how many people were in his army at each point and d) the temperature on the way back that killed off his army. At a glance you can see the factors that led to his army losing. AND it was drawn by hand in 1885 and is little more than a line drawing!
He also gives examples of really bad design, (including "the worst graphic ever to make it to print"), and shows what makes it so bad. His examples prove that information-less, counter-intuitive graphics can still look dazzlingly pretty, even though they're useless. In some examples, he shows how small changes can make the difference between an awful graphic and a really good one. My favourite example of this is how he drew the inter-quartile ranges on the x and y axes of a scatterplot, thus adding more information to the graphic without cluttering it up.
In summary, there's a lot more to good graphic design than being an Adobe guru. Reading this book made me feel like a more discerning viewer of graphics!
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267 of 278 people found the following review helpful By S. M Marson on March 1, 2002
Format: Hardcover Verified Purchase
Years ago, I purchased the first edition of VISUAL DISPLAY OF QUANTITATIVE INFORMATION. The second edition provides high-resolution color reproductions of the several graphics found in the first edition. In addition, corrections were made. However, to most readers/users, I doubt that the changes would be worthy of purchasing the second edition if one already owns the first edition.
Edward R. Tufte is a noteworthy scholar and the presentation of the material presented in this book is awe-inspiring. Tufte has also compiled two other books that can be best described as quite remarkable. These additional books are entitled, ENVISIONING INFORMATION and VISUAL EXPLANATIONS. All three of these volumes are not merely supplemental textbooks; they are works of art.
My intent was to use VISUAL DISPLAY OF QUANTITATIVE INFORMATION as part of teaching my statistics course. Students, but mostly faculty, are overly impressed with inferential statistics. Graphics play an important role in the understanding and interpretation of statistical findings. Tufte makes this point unambiguously clear in his books.
Two features of VISUAL DISPLAY OF QUANTITATIVE INFORMATION are particularly salient in teaching a statistics course. First, the concept of normal distribution is wonderfully illustrated on page 140. Here the reader is reinforced with the notion that in the normal course of human events, cultural/social/behavioral/ psychological phenomena usually fall into the shape of a normal distribution. The constant appearance of this distribution borders on miraculous. Just as importantly, it is the basis for accurate predications in all areas of science. Tufte's illustration (page 140) speaks to this issue much more clearly than a one-hour lecture on the importance of the normal distribution.
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280 of 296 people found the following review helpful By hunger on November 27, 2007
Format: Hardcover
I have a lot of mixed feelings about this book.

As a graphic designer and a minimalist, I love the way this book looks and I love the graphics Tufte's team has created.

Yet, the minimalist in me also dislikes Tufte's prose, which is surprisingly un-minimalist. The text is repetitive, and although Tufte does use this effectively at times to reiterate or summarize concepts, there are far more instances where I feel the repetition is simply irritating (Tufte's poems and block-quote summaries are, to me, good examples of this).

The minimalist in me is also not fond of the nature in which Tufte presents his opinions. Tufte makes frequent use of words like "lies" and "tricks," and while I am not fond of the targets of Tufte's derision, I feel that use of these words unnecessarily and unfairly assumes that poor graphs are always the result of malicious intent. Tufte's presentation as a whole, I feel, is often unnecessarily condescending (see e.g., p 120); indeed, Tufte seems to feel that unenlightened minds somehow deserve our ridicule and contempt.

As an academically oriented statistician, I also have mixed feelings. I give Tufte an immense amount of credit for opening a dialog about statistical graphics. And, I am grateful to him for pointing out the flaws and "wrongs" in the ways in which statistics are so often presented and suggesting ways in which these approaches can be changed. Moreover, I happen to agree tremendously with a large amount of what Tufte has to say, and often passionately so.

That said, I am puzzled by the amount of relevant concepts which are omitted from this text (or merely brushed over).
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