From: JROSSI@EAGLE.AAMRL.WPAFB.AF.MIL
Newsgroups: rec.music.synth
Subject: Re: Mark Fontana's survey (and the RESULTS thereof)
Date: 11 Sep 92 21:19:00 GMT


No, it would not surprise me to find out that some r.m.s readers are PhD
statisticians since we have a ton of PhD computer scientists, at least one
PhD Nuclear Physicist, and at least on PhD Neuropsychopharmacologist.  However,
having a PhD in a dicipline does not always assure that the lapses in
reasoning can occur.  For example, several months ago, xxx vos Savant (in
Parade magazine) made some remarks concerning probabilities of winning a
prize on a game show in which you can pick among 3 doors.  It went something
like ... After you made your pick, the host reveals that one of the doors
you did not pick was NOT the correct door.  While it was generally agreed that
the probability of picking the correct door was .33333 at the beginning of
the show, quite a fuss was made over the actually probability of having
picked the correct door (or whether to switch to another door) after one
door was revealed to be an incorrect choice.  Oddly, the new probability of
being correct after switching IS NOT .5.  It turns out (I forget what the
actual probability is) that you have a higher chance of winning if you
switch (actually, I think I only estimated the probability after running a
computer simul;ation of a couple hundred thousand repititions).  Anyway,
the important point is that the new probability is not .5.  In the next few
weeks, scores of PhD Statisticians wrote to Marilyn (thats xxxx) to tell her
how bad her probability reasoning was.  Unfortunately for them, they ended
up digesting a considerable amount of yoke.  The moral... a PhD in
statistics means that a considerable amount of book learning and a dissertation
was accomplished.  Nothing in the PhD promises that its holder is actually
a competent statistician.  I feel the same thing is true for neuropsycho-
pharmacologist PhD's as well (so don't feel like I am unjustly picking on
statisticians [however, I can't recall such a heated pronouncement of clearly
incorrect information as in the game show example by any group of influential
neuroscientists :-)  ]).  Anyway, because of the way r.m.s. is distributed
the entire readership is the population.  There is no generalization error
because the readership is not sampled.  Granted, there response bias problems
but, I doubt that you can point to real statistical data which suggests that
in a non-polarized poll as was Mark's, the results were affected by any other
variable than whether people could (a) care less or (b) have the time to
respond.  With this readership in the thousands, I would think that other
kinds of response biases are reduced to meaningless variables.  Now, I'm
sure that there is a document which you have read which you are only partially
rememberingf which discussed biased samples (or what not).  What Mark actually
did was a very stratified poll of an inclusive population.  I would assert
that without any rational reason to think otherwise, the probability of any
one r.m.s. reader to answer the question is, in the long run, independent of
the kind of interface he/she uses.  Remember, the key here is the lack of
polarization in the response vector.  For its intended purpose, Mark's survey
was as valid as it needed to be.  As someone else put it, the intent was not
to predict the economic viability of a set of interface manufacturers based
on the data.  The only intent was to secure some information concerning
what types of interfaces r.m.s. readers used and a reasonable estimate of
the numbers of each interface in use.

John