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The Visual Display of Quantitative Information
Tufte begins with the different kinds of informational graphics (maps, time-series, narratives, and relational graphics), describing their origins and evolution and presenting examples of excellence in their design. Many of these are fascinating in their own right -- two that I particularly appreciated were Minard's depiction of Napoleon's disastrous retreat from Moscow and an 11th century map of China.
"For many people the first word that comes to mind when they think about statistical charts is 'lie.'" Tufte gives examples of different kinds of deceit in graphics, along with some principles for maintaining graphical integrity. He goes on to consider the reasons for the poor quality of many informational graphics: one is the relegation of their design to those with art training but without an understanding of either the substance of the material or of quantitative (statistical) methods.
Part two begins by introducing some terminology and theory for describing graphics. The principle "Above all else show the data" is formalised as maximization of the data-ink ratio, and illustrated with some "before and after" examples of erasure of redundant or non-data-ink. Tufte excoriates various kinds of "chartjunk": moire vibration (the disconcerting effect caused by repeating patterns), the overuse of grids, and the "ducks" created when the design takes precedence over everything else.
Tufte gives specific suggestions for the design of box plots, bar charts, and scattergraphs. He argues for the use of multifunctioning graphical elements -- building data measures or grids out of the data itself, for example, by using labels that also show the end points of the data ranges. And he looks at ways of maximizing data density (within reason) and using "small multiples," or repeated smaller graphics. A final chapter steps back to consider the balance between text, text-tables, tables, semi-graphics, and graphics -- "Given their low data-density and failure to order numbers along a visual dimension, pie charts should never be used" -- and to touch on the aesthetics of proportion and scale.
All of this is liberally illustrated with examples, drawn from across the natural and social sciences. Despite the space devoted to these, The Visual Display of Quantitative Information packs a lot in, avoiding repetition or verbosity. Tufte's own tables and graphs are appropriately effective and the volume as a whole is elegantly put together: though it's more than that, it could be appreciated simply as a work of art. Tufte also finds room to survey publication practices across a select sample of international newspapers and journals, comparing the data density of graphics and the proportion of relational graphics (involving at least two variables that aren't temporal or spatial).
Most obviously, The Visual Display of Quantitative Information should be read by those involved in writing, editing, or designing documents or displays that contain statistical graphics -- from professional editors, technical writers, academics, and journalists right down to high school students. But others may appreciate it too: it has changed the way I look at informational graphics.
Danny has written over 700 book reviews. You can purchase The Visual Display of Quantitative Information from bn.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the (recently updated) book review guidelines, then visit the submission page.
The author was interviewed by the CAIB. He stated a lot of the information presented that lead the NASA managers to the "we can't do anything" approach was poorly designed and did NOT get information across, or was slanted. He pointed out several PowerPoint slides that had 10-12 errors on them that led to incorrect interpretations by the audience. This is a GREAT book, and should be on every engineer's shelf if they present data to an audience (including peers). MBA's study some of this in their classes, but (most) Engineers and Scientists and Doctors don't. It's a shame when you have great information that is hidden by poor presentation.
I thoroughly recommend this book to anyone who has to produce charts for their job.
I have recently converted to the Linux way of doing things, after being fed up with M$ for too long.
In my department, we use proprietary software for all of our data reporting. I would like to use an open source program instead, but since I'm new to Linux, I'm not sure what's out there.
I'm hoping the slashdot community can help me on this one- what are some good plotting programs that run on Linux?
I've written a small program for KDE that exhibits what I feel is a fairly novel method for representating hierarchical data graphically.
Currently it only shows information related to your filesystem, but with the next version it will begin accepting any kind of hierarchical data piped from the cli, via a text file, etc. (method of input as yet unfinalised).
If anyone's interested, here's a screenshot, and here's the homepage
I apologise for the plug; usually I'm quite good and wait for at least on-topic opportunities! I'm sure I'll still get the usual ac death threats etc. nothertheless I hope to have interested some people.
I got this book for Xmas a few years back and was a bit disappointed -- it is basically an "old school" version of Jakob Nielsen. The book was pretty and a somewhat interesting read with (as everyone always mentions) good historical examples, but expensive and ultimately not incredibly insightful. ET seems to have carved a good niche for himself making PowerPoint jockies feel part of a broader cultural tradition.
Sorry to be so negative.
Interesting that you should single out the map of Napoleon's retreat from Moscow. That graphic was the inspiration for our web log analysis program ClickTracks. Our CEO saw it and realised that what web log analysis needed was to show data in context, rather than in long lists. We have the poster of the Napoleon map on the wall of our office.
11.0010010000111111011010101000100010000101101000
Have a look at Tufte's sculptures too.
11.0010010000111111011010101000100010000101101000
Ah. I see.
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and on the second slide, you'd say
* = this book
. = other books reviewed here