Good online resource with tips on graphing association between two numeric variables under various conditions Context:
Over the while I've acquired a set of heuristics on how to effectively plot the association between two numeric variables. I imagine most people who work with data would have a similar set of rules.
Examples of such rules might be:


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*If one of the variables is positively skewed, consider plotting that axis on a log scale.

*If there are a lot of data points (e.g., n > 1000), adopt a different strategy such as using some form of partial transparency, or sampling the data;

*If one of the variables takes on a limited number of discrete categories, consider using a jitter or a sunflower plot;

*If there are three or more variables, consider using a scatterplot matrix;

*Fitting some form of trend line is often useful;

*Adjust the size of the plotting character to the sample size (for bigger n, use a smaller plotting character);

*and so on.


Question:
I'd like to be able to refer students to a web page or site that explains these and other tricks for effectively plotting associations between two numeric variables, perhaps with examples.


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*Are there any pages or sites on the internet that do a good job of this? 

 A: I can't think of great online resources off the top of my head, but a nice (and easily downloadable) book chapter that narrates how to visually explore a large, multidimensional data set in a thoughtful way is Brendan O'Connor and Lukas Biewald's chapter (warning: link is directly to a PDF) from Beautiful Data. The chapter is particularly useful as a teaching resource because it incorporates R code into the narrative.
Also, upon further reflection, I think John Tukey's classic "Some Graphic and Semigraphic Displays" (conveniently posted on Edward Tufte's website) is a really wonderful, albeit somewhat idiosyncratic, introduction to visualization.
For some reason, I seem to be thinking of book chapters...
A: Recent references:


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*Kelleher and Wagner 2011 "Ten guidelines for effective data visualization in scientific publications" provides a nice set of rules. The rules, with references (but not the full article) are available without subscription, although university students would likely have full access.

*United Nations 2009 "Making Data Meaningful" provides a nice overview, with rules and examples, including a section on 'emerging technologies'.
Older, but relevant resources


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*SIGGGRAPH provides some excellent tutorials, though lacking examples, including:


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*Senay and Ignatius 1999 "Rules and Principles of Scientific Data Visualization"

*Domik 1999 "Tutorial on Visualization"


*A good summary of Tufte can be found here:


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*Globus 1994 "Principles of Information Display for Visualization Practitioners"
