[R-sig-teaching] I need your thoughts on teaching with R

[Douglas Bates]

On Mon, Mar 30, 2009 at 5:29 PM, hadley wickham <h.wickham at gmail.com> 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 Even knowing how to look up numbers in a table is an outdated skill!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.)