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253 of 262 found the following review helpful:
1st edition compared to 2ndMar 01, 2002
By S. M Marson
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. Which goes to show -- once again -- "a picture is worth a thousand words." Sadly, the illustration on page 140 is small and in black and white. I wish the second edition included a larger reproduction of this photo. A color presentation would have been helpful.
Second, Tufte continues his unrelenting pattern to reinforce the importance and impact of illustrations in understanding complex concepts. In particular, page 176 demonstrates the impact of Napoleon's march to Moscow. The illustration is both profound and eerie. The reader is left with a feeling of death and pain for the foot soldiers...
241 of 254 found the following review helpful:
Mixed feelingsNov 27, 2007
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). Good examples include: samples versus populations, continuous versus categorical data, and exploratory graphics versus graphics presented for presentation.
For that reason, the academic and statistician in me is watchful of Tufte's role as an instructor of statistical ideas. Much of what Tufte has to say is not in fact unique or necessarily "right," and also not nearly close to being all there is to be said about statistical graphics (even at an introductory level). If students allow this text to be the sole contribution to their statistical education, I fear that -- without statistical intuition or knowledge to draw from -- they will not be critical statistical thinkers but blind followers. (Of course, none of this is intended to be a criticism of Tufte or Tufte's book.)
Those seeking a good overview of statistical graphics: keep in mind that this not strictly an instructional book. And while I wouldn't discourage you from reading or buying this text, I also wouldn't discourage you from seeking additional resources, either as an alternative or a supplement to Tufte's works. Much of the ideas supplied by Tufte here -- plus a great deal more -- can fundamentally be found in a good introductory statistical course or text, either directly or indirectly. Moreover, I would argue that there is absolutely no substitution for such an education.
50 of 55 found the following review helpful:
Superbly thought provokingSep 24, 2001
I divide my graphics work into two categories: BT (Before Tufte) and AT (After Tufte). I rarely acknowledge any involvement of a publication from those dark BT days.
Tufte's masterful and dead-on takes about how to communicate statistical and quantitative data challenges standard assumptions about developing graphical information and reveals, though it is not his stated intention, the weakness of so many graphics software packages. Just look at his collection of chartjunk and "ducks" (his term for hideous graphics) to see how all the whistles and bells available to us via computer graphics programs actually obfuscate the interpretation of visual information. By the time you read how much ink and paper are wasted by created bad graphics, you should be a convert.
And if you are ever lucky enough to have the chance to attend one of Tufte's seminars, pawn your PC if that's what it takes.
38 of 43 found the following review helpful:
It Will Change Your ThinkingMay 22, 2001
Are you put to sleep by briefings on a regular basis? Do they become more colorful and simplified as the intended audience rises in your company hirearchy? Do you feel that you are being talked down to by a lot of fluff that could be condensed by a factor of say, a million? If your answers are "yes," but you cannot provide a good alternative, then this is the book for you. It changes the way you look at data. Through numerous examples, Tufte demonstrates how to rearrange and simplify tabulated lists, schedules, graphs, diagrams and maps in a way that elegantly reveals otherwise hidden relationships and patterns. I have applied his techniques to my own briefings as well as to vacation itineraries, meeting notes, and to do lists. But be forewarned. I have touted this book to my peers and managers and of the four people who have read the book none have had the epiphany I experienced. This book may be only for those who are fed up enough to change.
20 of 21 found the following review helpful:
Changed my styleJun 10, 2006
By Jeffrey Jones
I was one of those chart-makers who used color just because I could, even when it was unnecessary or even inappropriate. This book changed the way I looked at graph-making. His concepts of data per unit of ink (which should be maximized), and trying to make each droplet of ink convey something useful were extremely helpful, as were his suggestions to minimize distractions and phony 3-d effects.
This, and his second book, "Envisioning Information" are must-reads for anyone designing computer statistical tools (like I was) or simply trying to convert raw data into meaningful graphs, maps, etc.
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