> 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Even knowing how to look up numbers in a table is an outdated skill!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) > 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! Hadley -- http://had.co.nz/ _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-teaching
