Friday, February 8, 2013

Fun with charts

This post by Daniel Kuehn is worth reading, although all of the action is in the comments. 

I think he is right on about the denomintor problem in interpreting her graphs.  It's also a very good example of when a point can be correct and yet not explain all of the differences (her comments about rounding).  However, the labeled buldge seems to be a lesser sin than variable bracket sizes on a density plot.

As for the change argument, it is fine to use a chart to explain something and then talk about the expected changes to the distribution.  Where I am less happy is that there are changes going on in the United States all of the time (aging of the population, propensity to form a new household) that are going to influence the shape of this curve.  It is possible to imagine the curve shifting exactly as Jon Evans suggested, and the reasons having to do with factors that have nothigng to do with inequality.

But standardized curves have their own issues . . .  So even Magan's use of the curve to show the shifts over time doesn't address the null conditional on the changes in the underlying population.  This may even help her argument, I am not sure, but certainly I would rather graph density plots in equal sized segments just for reader clarity

Still, a worthwhile argument to follow and it is useful insofar as it improves understanding of what the plots do and do not mean. 

1 comment:

  1. I highly recommend going to

    http://www.census.gov/hhes/www/income/data/historical/household/

    and playing around with the tables yourself. For starters, take a look at what you get when you plot out all of the points for 35K to 50K, 50K to 75K and the top group.

    All of Joseph's caveats apply, but it looks like something is going on.

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