The Visual Display of Quantitative Information Author: Edward R. Tufte | Language: English | ISBN:
0961392142 | Format: EPUB
The Visual Display of Quantitative Information Description
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.
- Hardcover: 200 pages
- Publisher: Graphics Pr; 2nd edition (May 2001)
- Language: English
- ISBN-10: 0961392142
- ISBN-13: 978-0961392147
- Product Dimensions: 10.8 x 8.8 x 0.8 inches
- Shipping Weight: 2.2 pounds (View shipping rates and policies)
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.
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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