> Thanks for trying this, Hadley, because the comparison > is instructive in terms of the difference between the > communication goals of analysis and presentation graphs.
Yes, and I think it's a difference that not enough people are familiar with. > Actually, one should regard income as the independent variable, > deaths as response, so what you want is > > > ggplot(csr, aes(y=deaths, x=income)) + > + geom_path(colour="grey80") + geom_point() > > > but, instead of/in addition to geom_path, a bolder loess smooth > would show the trend better. + geom_smooth() will add a loess smooth to the above plot. > This does, indeed show the inverse, and non-linear relation > between welfare income and deaths more directly, a few outliers. > Good for an analysis graph, but it fails the Interocular Traumatic > Test for a presentation graph-- the message should hit you between > the eyes. But unless you trust the source of the presentation graph, one needs the analysis graph to be sure that IOT isn't caused by manipulation of the data. Hadley -- http://had.co.nz/ ______________________________________________ R-help@r-project.org 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.
