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

[hadley wickham]

> 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Even knowing how to look up numbers in a table is an outdated skill!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/