Hello, I apologize that this is off-topic. I am seeking information on perception of graphical data, in an effort to improve the plots I produce. Would anyone point me to literature reviews in this area? (Or keywords to try on google?) Is this located somewhere near cognitive science, psychology, human factors research? For example, some specific questions I have are: I recall as a child when I first saw a map where the areas of the containers (geographical states) were drawn as rectangles, proportional to a quantity other than land area. Does anyone know of an algorithm for drawing such maps? Would anyone know of a journal or reference where I can find studies on whether subjects reading these maps can accurately assess the meaning of the different areas, as [some of us] can assess different heights on a bar graph? (What about areas in bar graphs with non-uniform widths?) Scatter plots of microarray data often attempt to represent thousands or tens of thousands of points, but all I read from them are density and distribution --- the gene names cannot be shown. At what point, would a sunflowerplot-like display or a smooth gradient be better? When two data points drawn as 50% gray disks are small and tangent, are they perceptually equivalent to a single, 100% black disk? Or a 50% gray disk with twice the area? What problems are known about plotting with disks --- do viewers use the area or the diameter (or neither) to gauge weight? As you can tell, I'm a non-expert, mixing issues of data interpretation, visual perception, graphic representation. Previously, I didn't have the flexibility of R's graphics, so I didn't need to think so much. I've read some of Edward S. Tufte's books, but found them more qualitative than quantitative. Thanks! Richard 212-933-3305 / richard.c.yeh at bankofamerica.com
You might want to look at the cartogram literature. See e.g. http://www-personal.umich.edu/~mejn/election/ I don't know of an R implementation of this sort of thing, but perhaps others can correct me. url: www.econ.uiuc.edu/~roger Roger Koenker email rkoenker at uiuc.edu Department of Economics vox: 217-333-4558 University of Illinois fax: 217-244-6678 Champaign, IL 61820 On Aug 24, 2007, at 12:30 PM, Yeh, Richard C wrote:> Hello, > > I apologize that this is off-topic. I am seeking information on > perception of graphical data, in an effort to improve the plots I > produce. Would anyone point me to literature reviews in this > area? (Or > keywords to try on google?) Is this located somewhere near cognitive > science, psychology, human factors research? > > For example, some specific questions I have are: > > I recall as a child when I first saw a map where the areas of the > containers (geographical states) were drawn as rectangles, > proportional > to a quantity other than land area. Does anyone know of an algorithm > for drawing such maps? Would anyone know of a journal or reference > where I can find studies on whether subjects reading these maps can > accurately assess the meaning of the different areas, as [some of us] > can assess different heights on a bar graph? (What about areas in bar > graphs with non-uniform widths?) > > Scatter plots of microarray data often attempt to represent > thousands or > tens of thousands of points, but all I read from them are density and > distribution --- the gene names cannot be shown. At what point, > would a > sunflowerplot-like display or a smooth gradient be better? When two > data points drawn as 50% gray disks are small and tangent, are they > perceptually equivalent to a single, 100% black disk? Or a 50% gray > disk with twice the area? What problems are known about plotting with > disks --- do viewers use the area or the diameter (or neither) to > gauge > weight? > > > As you can tell, I'm a non-expert, mixing issues of data > interpretation, > visual perception, graphic representation. Previously, I didn't have > the flexibility of R's graphics, so I didn't need to think so much. > I've read some of Edward S. Tufte's books, but found them more > qualitative than quantitative. > > Thanks! > > Richard > > 212-933-3305 / richard.c.yeh at bankofamerica.com > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting- > guide.html > and provide commented, minimal, self-contained, reproducible code.
Hi,
You may want to check chapter 4 ("Graphical Perception") in W. S.
Cleveland (1985?) "The Elements of Graphing Data" and the references
he includes.
Regards,
--
David
On 8/24/07, Yeh, Richard C <richard.c.yeh at bankofamerica.com>
wrote:> Hello,
>
> I apologize that this is off-topic. I am seeking information on
> perception of graphical data, in an effort to improve the plots I
> produce. Would anyone point me to literature reviews in this area? (Or
> keywords to try on google?) Is this located somewhere near cognitive
> science, psychology, human factors research?
>
> For example, some specific questions I have are:
>
> I recall as a child when I first saw a map where the areas of the
> containers (geographical states) were drawn as rectangles, proportional
> to a quantity other than land area. Does anyone know of an algorithm
> for drawing such maps? Would anyone know of a journal or reference
> where I can find studies on whether subjects reading these maps can
> accurately assess the meaning of the different areas, as [some of us]
> can assess different heights on a bar graph? (What about areas in bar
> graphs with non-uniform widths?)
>
> Scatter plots of microarray data often attempt to represent thousands or
> tens of thousands of points, but all I read from them are density and
> distribution --- the gene names cannot be shown. At what point, would a
> sunflowerplot-like display or a smooth gradient be better? When two
> data points drawn as 50% gray disks are small and tangent, are they
> perceptually equivalent to a single, 100% black disk? Or a 50% gray
> disk with twice the area? What problems are known about plotting with
> disks --- do viewers use the area or the diameter (or neither) to gauge
> weight?
>
>
> As you can tell, I'm a non-expert, mixing issues of data
interpretation,
> visual perception, graphic representation. Previously, I didn't have
> the flexibility of R's graphics, so I didn't need to think so much.
> I've read some of Edward S. Tufte's books, but found them more
> qualitative than quantitative.
>
> Thanks!
>
> Richard
>
> 212-933-3305 / richard.c.yeh at bankofamerica.com
>
> ______________________________________________
> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
Dear Richard, Though slightly dated, the following article is a nice summary of the literature on graphical perception: Lewandowsky, S & Spence, I. (1989) The perception of statistical graphs. Sociological Methods and Research, 18, 200-242. I hope this helps, John On Fri, 24 Aug 2007 13:30:56 -0400 "Yeh, Richard C" <richard.c.yeh at bankofamerica.com> wrote:> Hello, > > I apologize that this is off-topic. I am seeking information on > perception of graphical data, in an effort to improve the plots I > produce. Would anyone point me to literature reviews in this area? > (Or > keywords to try on google?) Is this located somewhere near cognitive > science, psychology, human factors research? > > For example, some specific questions I have are: > > I recall as a child when I first saw a map where the areas of the > containers (geographical states) were drawn as rectangles, > proportional > to a quantity other than land area. Does anyone know of an algorithm > for drawing such maps? Would anyone know of a journal or reference > where I can find studies on whether subjects reading these maps can > accurately assess the meaning of the different areas, as [some of us] > can assess different heights on a bar graph? (What about areas in > bar > graphs with non-uniform widths?) > > Scatter plots of microarray data often attempt to represent thousands > or > tens of thousands of points, but all I read from them are density and > distribution --- the gene names cannot be shown. At what point, > would a > sunflowerplot-like display or a smooth gradient be better? When two > data points drawn as 50% gray disks are small and tangent, are they > perceptually equivalent to a single, 100% black disk? Or a 50% gray > disk with twice the area? What problems are known about plotting > with > disks --- do viewers use the area or the diameter (or neither) to > gauge > weight? > > > As you can tell, I'm a non-expert, mixing issues of data > interpretation, > visual perception, graphic representation. Previously, I didn't have > the flexibility of R's graphics, so I didn't need to think so much. > I've read some of Edward S. Tufte's books, but found them more > qualitative than quantitative. > > Thanks! > > Richard > > 212-933-3305 / richard.c.yeh at bankofamerica.com > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code.-------------------------------- John Fox, Professor Department of Sociology McMaster University Hamilton, Ontario, Canada http://socserv.mcmaster.ca/jfox/
Hi Richard,> I apologize that this is off-topic. I am seeking information on > perception of graphical data, in an effort to improve the plots I > produce. Would anyone point me to literature reviews in this area? (Or > keywords to try on google?) Is this located somewhere near cognitive > science, psychology, human factors research?Probably the best place to start on these general issues, are a couple of papers by Cleveland: @article{cleveland:1987, Author = {Cleveland, William and McGill, Robert}, Journal = {Journal of the Royal Statistical Society. Series A (General)}, Number = {3}, Pages = {192-229}, Title = {Graphical Perception: The Visual Decoding of Quantitative Information on Graphical Displays of Data}, Volume = {150}, Year = {1987}} @article{cleveland:1984, Author = {Cleveland, William S. and McGill, M. E.}, Journal = {Journal of the American Statistical Association}, Number = 387, Pages = {531-554}, Title = {Graphical Perception: Theory, Experimentation and Application to the Development of Graphical Methods.}, Volume = 79, Year = 1984} For colour in particular, I like Ross Ihaka's introduction to the subject: @inproceedings{ihaka:2003, Author = {Ihaka, Ross}, Booktitle = {Proceedings of the 3rd International Workshop on Distributed Statistical Computing (DSC 2003)}, Title = {Colour for Presentation Graphics}, Year = {2003}} and also see colorbrewer.org> Scatter plots of microarray data often attempt to represent thousands or > tens of thousands of points, but all I read from them are density and > distribution --- the gene names cannot be shown. At what point, would a > sunflowerplot-like display or a smooth gradient be better? When two > data points drawn as 50% gray disks are small and tangent, are they > perceptually equivalent to a single, 100% black disk? Or a 50% gray > disk with twice the area? What problems are known about plotting with > disks --- do viewers use the area or the diameter (or neither) to gauge > weight?I think many of these are still research topics. Two (of many) places to start are: @article{huang:1997, Author = {Huang, Chisheng and McDonald, John Alan and Stuetzle, Werner}, Journal = {Journal of Computational and Graphical Statistics}, Pages = {383--396}, Title = {Variable resolution bivariate plots}, Volume = {6}, Year = {1997}} @article{carr:1987, Author = {Carr, D. B. and Littlefield, R. J. and Nicholson, W. L. and Littlefield, J. S.}, Journal = {Journal of the American Statistical Association}, Number = {398}, Pages = {424-436}, Title = {Scatterplot Matrix Techniques for Large N}, Volume = {82}, Year = {1987}}> As you can tell, I'm a non-expert, mixing issues of data interpretation, > visual perception, graphic representation. Previously, I didn't have > the flexibility of R's graphics, so I didn't need to think so much. > I've read some of Edward S. Tufte's books, but found them more > qualitative than quantitative.More quantitative approaches are Cleveland's, Bertin's and Wilkinson's: @book{cleveland:1993, Author = {Cleveland, William}, Publisher = {Hobart Press}, Title = {Visualizing data}, Year = {1993}} @book{cleveland:1994, Author = {Cleveland, William}, Publisher = {Hobart Press}, Title = {The Elements of Graphing Data}, Year = {1994}} @book{chambers:1983, Author = {Chambers, John and Cleveland, William and Kleiner, Beat and Tukey, Paul}, Publisher = {Wadsworth}, Title = {Graphical methods for data analysis}, Year = {1983}} @book{bertin:1983, Address = {Madison, WI}, Author = {Bertin, Jacques}, Publisher = {University of Wisconsin Press}, Title = {Semiology of Graphics}, Year = {1983}} @book{wilkinson:2006, Author = {Wilkinson, Leland}, Publisher = {Springer}, Series = {Statistics and Computing}, Title = {The Grammar of Graphics}, Year = {2005}} Hope this gets you started! Hadley -- http://had.co.nz/