On Mon, Mar 30, 2009 at 5:29 PM, hadley wickham <[email protected]> wrote: >> What do I mean by simplify? There are many topics in an introductory >> statistics course that are ingrained in the curriculum but really are >> there for the sake of approximation or computational simplification. >> How many introductory texts still describe how to approximate a >> "difficult" distribution by a "simpler" distribution (hypergeometric >> by binomial, binomial by Poisson or Gaussian, etc.)? When you can >> calculate the exact probability why do you want to waste time teaching >> an approximation and rules like "when np > 5 ..."? Even a basic > > Even knowing how to look up numbers in a table is an outdated skill! > >> graphical presentation, the histogram, is outmoded. The purpose of >> the histogram is to give us a picture of the density. Why not use a >> density plot for this? There is a great advantage in that you can >> easily overlay density plots from different groups, not to mention the >> fact that it shows a smooth approximation to the density. In the past >> we used histograms because it was comparatively simple to choose bins >> and count the observations in the bins then produce a bar chart. We >> can do better than that now.
> I agree 100% with your points apart from this one. I'm not a big fan > of density estimates because most real-life distributions are not > smooth, continuous and unbounded, like most density estimators assume > they are. It's also much harder to understand how a density plot is > made, and while I don't think students need to understand the > motivations and theory for every tool they use, I think they should > understand how their basic graphic tools work. A happy intermediate > is the frequency polygon, which has more favourable theoretical > properties than the histogram, but is equally easy to understand (and > you can overlay them like densities) Good point. Density plots do have problems with smearing at the boundaries. >> I have over the years produced slides for classes based first on >> Devore's books then on Peter's book and now on the Cohen and Cohen >> book. I am willing to make these available, including the source >> code, so others can borrow code or presentation approaches if they >> wish. I am not familiar with open documentation licenses like >> Creative Commons. If it would help to stimulate discussion I will >> make them available without copyright. I would be particularly >> interested in corresponding with potential text book authors on some >> of the techniques that I think can be used to simplify presentation of >> R code and graphics. I don't have plans to embark on writing a text >> myself. > > I would love to see these! The source directory of my slides for Peter's book, "Introductory Statistics with R", is available as http://www.stat.wisc.edu/~bates/ISwR.zip (I'm sorry, Hadley, but I use lattice throughout. I haven't taken the time to learn ggplot2.) _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
