Politically correct way of ordering stacked barplots? What is the politically correct way of ordering stacked barplots that contain gender statistics? For example, in a stacked barplot for the number of grantees of a fellowship program, should one put male or female on the bottom? How about left/right if it's on horizontal bars?
 A: I would argue against any stacked bar plots! I would, instead, make separate bars for men and women. If you just have two bars and two levels, it's not so bad, but stacked bar plots are often hard to read. 
A: In a stacked barplot, put the largest category (the one with the greater number of occurrences) on bottom. The criterion here is readability.
In horizontal bars (the bars are horizontal), put the largest category on top. Again, the criterion is readability.
In histograms (vertical bars), use alphabetical order. Men/Women or Female/Male, it doesn't matter. The criterion here is political correctness, which is another way of saying that we try to avoid offending those who are easily offended.
A: It's true that we live in politically correct times; for the most part, in my honest opinion, that's probably a good thing, but it certainly does get out of hand sometimes.  Nonetheless, I have great difficulty envisioning any real-world scenario in which you will get in trouble for having put males or females on top in a stacked bar chart.  So, I will give here some general advice about displaying data that I've given to people from time to time (actually, much of this may be more relevant to non-stacked bar plots, dot plots, or other graphics, but could apply to stacked bar plots as well):  


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*Think about the story you are trying to tell.  Lets say that you are arguing that women are being given fewer grants than men, and you suspect discrimination.  Then you are using men as the basis for comparison, or the default.  In this situation, I would put men first, and women second.  I can equally well tell a story that compares men to women, where they are the default, and then I would put women first.  Likewise, when comparing several different types of treatments to a control, it is often intuitive to put the control first, and there may well be an intuitive ordering of the remaining treatments based on the story you are telling.  

*With very many groups (n.b., not the case here) ordering by magnitude often aids clarity.  For example, if you wanted to list the proportion of grants to women for each state in America (i.e., 50 bars), the figure may be more readable if you sort the list into either ascending or descending order by percentage (choosing asc vs. desc by #1).  

*Make your figures consistent with each other.  Quite commonly, you will have more than one figure.  Try to make them as similar as possible.  For instance, put the groups in the same order in each graph.  Likewise, if you use color, give the same groups the same colors in each graph.  This strategy will ease the cognitive workload of your readers / audience; I don't know how many times I've seen one graph where men are blue & women red and then the next one men are red & women blue--it makes it very difficult to keep track of what's going on.  Even adding redundant coding (e.g., color or crosshatching, etc.) that isn't strictly needed can help people absorb the big picture quickly and easily.  

