This thread has certainly been an interesting one, particularly the
discussion about sorting out the use of t and z tests for the mean. It's
not only in texts for psychology students that the authors present the n
> 30 'rule' as a law of nature cast in bronze and elevated to the peerage! Apart from
>anyuthing else, these authors confuse two quite separate things - the effect of the
>central limit theorem, which allows large n to compensate for non normality, and the
>effect of using s to estimate sigma when it is not known. Since the latter requires
>normality to justify the t test, the central limit theorem can be used to justify its
>use for large n. Switching from t to z then is a matter of what 'close enough' means
>to the user. For me, that comes for about n = 200, certainly not anywhere near n = 30.
The annoying thing is that there is absolutely no advantage in switching
to the normal and using this as an approximation, if you have
appropriate tables, or if using a computer. In the latter case you might
as well stick with the t always.
One of the problems with teaching rules is that the rules usually
require so many qualifications and allowances for different
circumstances that they become non-simple. (Particualry when people make
them even more complicated than they need to be by getting confused
themselves, as with the Z and t.)
On the other hand, a body of knowledge can be thought of as a set of
'rules'. The important thing is that this set is constructed by the
individual, so our aim should not be to teach statistics as a set of
rules, but in such a way that each student can develop his or her own
set of rules. They won't be the same for all, and they will different
from the teacher's, but they hopefully will work. (If you like, this is
a defintion of a 'good student' - one who manages to construct a
successful set of rules for each subject.
Merry Christmas to all.
Alan
Robert Frick wrote:
>
> I happened to have a vehement and probably radical opinion on this.
> One of my sayings: "Ironically, our educational system is ideally suited
> to teaching computers and ill-suited to teaching human beings." If you
> are going to program a computer to do statistics, tell the computer
> rules to follow.
>
> If you give students rules to memorize, they will surely forget them.
> If you had a student who learned and applied the rules, people would say
> that the student was mindlessly following rules and couldn't think for
> him/herself. But your best student will just remember half the rules --
> and by that, I mean half of each rule.
>
> I know it is hard to make statistics fun, but FOLLOWING RULES IS NEVER
> FUN. Not in math, not in games, nowhere.
>
> There are advantages to teaching rules. Most students like it. They
> certainly understand that method of teaching. They just won't learn
> anything.
>
> Bob F.
>
> EAKIN MARK E wrote:
> >
> > I just received a review which stated that statistics should not be
> > taught
> > by the use of rules. For example a rule might be: "if you wish to
> > infer
> > about the central tendency of a non-normal but continuous population
> > using
> > a small random sample, then use nonparametrics methods."
> >
> > I see why rules might not be appropriate in mathematical statistics
> > classes where everything is developed by theory and proof. However I
> > teach
> > statistical methods classes to business students.
> >
> > It is my belief that if faculty do not give rules in methods classes,
> > then
> > students will infer the rules from the presentation. These
> > student-developed rules may or may not be valid.
> >
> > I would be intested in reading what other faculty say about
> > rule-based teaching depending on whether you teach theory or methods
> > classes.
> >
> > Mark Eakin
> > Associate Professor
> > Information Systems and Management Sciences Department
> > University of Texas at Arlington
> > [EMAIL PROTECTED] or
> > [EMAIL PROTECTED]
--
Alan McLean ([EMAIL PROTECTED])
Acting Deputy Head, Department of Econometrics and Business Statistics
Monash University, Caulfield Campus, Melbourne
Tel: +61 03 9903 2102 Fax: +61 03 9903 2007
