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The Visual Display of Quantitative Information Hardcover – 1 Feb 1992

4.5 out of 5 stars 50 customer reviews

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Hardcover, 1 Feb 1992
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Product details

  • Hardcover: 197 pages
  • Publisher: Graphics Press USA; Reprinted edition edition (Feb. 1992)
  • Language: English
  • ISBN-10: 096139210X
  • ISBN-13: 978-0961392109
  • Product Dimensions: 2.5 x 22.9 x 27.9 cm
  • Average Customer Review: 4.5 out of 5 stars  See all reviews (50 customer reviews)
  • Amazon Bestsellers Rank: 334,868 in Books (See Top 100 in Books)
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Product description

The Visual Display of Quantitative Information 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.

Customer Reviews

4.5 out of 5 stars
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Top Customer Reviews

Format: Hardcover Verified Purchase
The book is simply stunning. It consigns most of the graphical designs of the consulting industry into the dustbin of bad practice and presents some slightly unconventional alternatives, which actually do look more compelling on second thought. The standard rules of avoiding lie factors in graphics, maximising the data / ink ratio, the integration of graphics and text are all spot on and show how statistics, when done right, is far from boring, tending far more towards the fascinating instead.

The book also provides some splendid examples of good graphical design, shockingly most of them fairly old - i.e. the field did not progress nearly as much as should be expected, with most of the progress being pre-20th century, with several unfortunate steps back from the 1920s to 1970s (shown as well). Another interesting facet is the historical development of methods for presenting quantitative information, which is interesting in its own right.

This book should be essential reading for anyone who relies on visually presenting quantitative information and is an absolute must in management consulting.
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Format: Hardcover Verified Purchase
The reproductions are wonderful and the text is informative. A great book to have and read. Get it now!

A classic for every thinking-man's shelf!
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Format: Hardcover
This book, and the two companion volumes ("Envisioning Information" and "Visual Explanations") are must-haves for anyone who is in the business or producing or interpreting
statistical information.

Tufte starts with a simple proposition: graphs and graphics
that represent statistical data should tell the truth. It's
amazing how often designers of such graphics miss this basic
point. Tufte clearly and entertainingly elucidates the most
common "graphical lies" and how to avoid them.

Read this
book and you'll never look at a newspaper or presentation
graphics the same way again -- you'll be left wondering if
the author *intended* to lie about what the data were saying, or if he/she just didn't know any better.

Another reviewer claimed that this book talks about how to make graphics accurate, not beautiful. He's right in some sense, but who cares? There are a million books on how to make "pretty" graphical displays, but precious few on how to make useful ones. These books are they.
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Format: Hardcover
This book should be a compulsory read for all graphic designers dealing with data visualisation.
The clearly focused chapters, all with superb illustrations, take the reader through some of the best and worst graphics and charts ever printed, with Tufte providing crystalline insights and techniques that will stick in your mind and make your own work better.
Whilst this book deals only with printed graphics, I think that the lessons learned are even more valuable as a foundation for interactive media designers. With the added dimensions of time and user involvement comes the potential to commit far worse design-crimes than many of the examples laid bare in this book!
Like I said: Read it before you make a really bad mistake!
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Format: Hardcover
This is the first of Edward Tufte's brilliant trilogy on how information should be displayed. The Visual Display of Quantitative Information is about pictures of numbers. Envisioning Information is about picturing nouns. Visual Explanations is about picturing verbs. All three are beautiful artefacts in their own right, encapsulating the author's ideas in the actual production of the book. Each is crammed with examples of good and bad practice over the past centuries.
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Format: Hardcover Verified Purchase
This book has good and bad aspects. First let me look at the bad part: the text Tufte has written. The problem is, most of it is founded on a single principle: maximise the information-to-ink ratio. Now as a scientist myself, this sounded like a great idea. It would not just improve your graphs (and similar diagrams), but do it in a fairly systematic way. Why add more stuff to your graph if it doesn't add any more information? It will only confuse the reader for no benefit. It seems so simple. So obvious. And yet it is 100% wrong.

The problem with this idea is that it is based on a fundamentally flawed view of human perception. We don't just see individual blobs of inks (or darkened pixels), so that adding more makes it harder. Instead we see the various shapes they form (search the web for "Kanizsa's triangle"!), and we should be aiming to reduce the complexity of this. For example, if you have several graphs next to each other, then putting a box around each will keep them visually distinct, so you can focus on one at a time with no conscious effort. If you leave out the bounding boxes then they become a jumble of tiny objects that take some effort to group visually. A very small amount of effort, admittedly, but you've made it harder for no reason. But Tufte HATES putting boxes around things! After all, you've certainly added more ink, and added no more information, so by his flawed rule you have made things unambiguously worse.

So now for the good. Why should you buy this book if not to read it? Because it is filled with pictures representing data from a myriad of sources. Some of them are effective, some are not. Some are beautiful, some are ugly. All are worth reflecting on.

In conclusion: Ok, I exaggerate when say "do not read it".
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