I am writing a CS paper, I usually would assume anyone knows what a boxplot is in a technical domain. Is a reference required or are boxplots knowledge that can be assumed? What is essential to explain about a boxplot in this setting?
1 Answer
I recommend that you be explicit about all elements of the plot. Explain how the boxplot indicates the median (mean?), quartiles (quantiles?), and extreme values (distant quantiles?)... assuming that's what you're plotting. I suggest you be explicit here not only for clarity, but also because the general boxplot template can be used to display different statistics together. The wikipedia article discusses some variations.
You will rarely be criticized for being too explicit, but it's easy to criticize for being too ambiguous. As a rule of thumb, make as few assumptions about your readers as possible.
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$\begingroup$ Also there are different conventions for how to draw boxplots: What defines an outlier, how is the mean or standard deviation indicated (if they are) etc... Even in disciplines where boxplots are more common it would seem to be useful to explain your boxplots. $\endgroup$ Commented Nov 13, 2013 at 5:11
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2$\begingroup$ Explanation of boxplots is usually poor, a situation that perpetuates itself in several literatures. In particular, the Tukey convention that points are shown individually if and when more than 1.5 IQR from the nearer quartile is (a) not universal (b) not something that can be assumed obvious. stata-journal.com/sjpdf.html?articlenum=gr0039 is one reference discussing variations, which gives others. $\endgroup$– Nick CoxCommented Nov 13, 2013 at 9:14
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1$\begingroup$ In addition to Nick's article I would suggest Hadley Wickham and Lisa Stryjewski's pre-print, 40 years of box-plots. $\endgroup$– Andy WCommented Nov 13, 2013 at 13:25
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2$\begingroup$ (+1) When explaining boxplots--which nowadays are almost always created by software--it is important to understand the software's conventions. Thus I would not recommend consulting Wikipedia, but instead look at your software manual. If that is not sufficient, some reverse-engineering (by constructing boxplots of tiny datasets where the computations are easily emulated by hand) usually reveals the details. $\endgroup$– whuber ♦Commented Nov 13, 2013 at 16:09
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$\begingroup$ @Andy W The paper you cite appears to be dormant. I think it fair to mention that Hadley Wickham posted on GitHub not only the paper, but also two reviews from the American Statistician and two comments sent privately and independently to him by David Hoaglin and myself. See e.g. github.com/hadley/boxplots-paper/blob/master/reviews/… You can form your own judgements. $\endgroup$– Nick CoxCommented Nov 13, 2013 at 16:50