HDTenEightyP/NetNews huggingface dataset:
Newsgroups: bit.listserv.edstat-l
Date:         Mon, 12 Oct 1992 09:50:00 PDT
Reply-To:     Albyn Jones <jones@REED.EDU>
From:         Albyn Jones <jones@REED.EDU>
Subject:      esoterica

Murray A. Jorgensen [ maj@waikato.ac.nz ]   writes:
>
>
>Like Arnie, I have been having some difficulty appreciating
>all this discussion of the envelope problem. To spend a large
>proportion of class time on explaining the difference between
>various systems of statistical inference seems to me like
>attending to the needs of the instructor, rather than most
>consumers of statistics. Certainly this may be appropriate to
>explore later in the education of a statistical specialist, but
>I don't think that was what most people were talking about.
>
>Isn't _any_ form of interval estimate an interval within
>which it is reasonable to expect the parameter to lie?
>
>Can anyone think of a situation where a user of statistics
>would come to serious harm in thinking that a parameter
>belonged to a particular 95% confidence interval with
>probability .95?

Most of the time in science there is no well specified loss function,
so its hard to compute the damage done by misunderstanding
confidence intervals.  It seems sensible to treat a CI as an estimate
of the  range of plausible values for the parameter, assuming that
the model is correctly specified.  Any more than that seems a bit
optimistic to me.

Lets extend the "who cares what it really means" argument just a bit
farther, to hypothesis tests.  why bother to get it right here either?
After all, the .05 level hypothesis test for \mu = 0 is  just the answer
to the question "is 0 in the 95% CI for \mu?". What's wrong with students
thinking that the p-value is the probability that the null hypothesis is
true?  Why ask them to worry about strange connundrums, such as the
possibility that repeated failures to reject a null hypothesis might
not be strong evidence that the null hypothesis is true?

Surely no harm can come from misunderstanding esoterica like this!
Who cares if students understand the logic of inference, so long as they
can churn out CI's and p-values?

albyn jones
jones@reed.edu
From: maj@waikato.ac.nz
Newsgroups: bit.listserv.edstat-l
Subject: Niceties of inference schools
Date: 12 Oct 92 09:48:24 +1300
Organization: University of Waikato, Hamilton, New Zealand

Replying to Arnie Kahn, Albyn Jones writes:

   The envelope problem may sound like 
	esoterica, but it raises basic
   issues about statistical inference.  
	Its a great example to discuss
   in a course, as it will generate 
	lots of interest and interaction.
   What more could an instructor ask 
	from an example?  It seems
   exactly analogous to discussion of "how 
	to explain correlation", you may
   get some idea for your courses from either discussion.
	

Like Arnie, I have been having some difficulty appreciating
all this discussion of the envelope problem. To spend a large
proportion of class time on explaining the difference between
various systems of statistical inference seems to me like
attending to the needs of the instructor, rather than most
consumers of statistics. Certainly this may be appropriate to
explore later in the education of a statistical specialist, but
I don't think that was what most people were talking about.

Isn't _any_ form of interval estimate an interval within
which it is reasonable to expect the parameter to lie?

Can anyone think of a situation where a user of statistics
would come to serious harm in thinking that a parameter
belonged to a particular 95% confidence interval with
probability .95?
-- 
Murray A. Jorgensen [ maj@waikato.ac.nz ]    University of Waikato
Department of Mathematics and Statistics     Hamilton, New Zealand      
__________________________________________________________________
'Tis the song of the Jubjub! the proof is complete,
if only I've stated it thrice.'
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Date:         Tue, 13 Oct 1992 07:05:29 +0200
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From:         BOKKIE@UCTVAX.UCT.AC.ZA
Subject:      Re: Are you teaching what you think

I too, have often experienced the following:

> ... one problem I have frequently seen in many of these courses
> concerns the research project where the "correct" analytical technique
> is outside the scope of the course (and often outside the scope
> of the teacher's background).  Usually the teacher tells the student
> to analyze the data in a simplistic "incorrect" manner in order to
> stay within the realm of the course.

I have no answers, only a point to add:  It is perhaps unfair to
the student concerned, vis-a-vis the rest of the class, to expect
him/her to spend extra time and effort mastering the correct method
of analysis which was not taught.  Furthermore, unfair to the
rest of the class who do not get the benefit of this extra tuition.

Our Honours (postgrad) students must complete an independent research
project as a major part of their training.  At the end of the year
we hold a colloquium where each student presents in public a short
account of their research.  In such a situation the student who has
used complicated statistical techniques would stand out more, and
appear superior to the others. Sometimes there is quite strong
competition between students ...

Frank Bokhorst
Psychology Department
University of Cape Town
Newsgroups: bit.listserv.edstat-l
Date:         Wed, 7 Oct 1992 13:06:26 CDT
Reply-To:     WMILLER@UAFSYSB.BITNET
From:         WMILLER@UAFSYSB.BITNET
Subject:      USEFUL TEACHING TOOL

Hi,

I found the discussion on gender very interesting.  It was also very
illustrative of the research dialogue that happens in "real" research.
With that in mind I have forwarded many of these postings to my methods
class.  They all have user accounts and I think will be informed by
the discussion.  I believe that it helps them understand that even
real statisticians may come to differing conclusions about the same
data.

Thanks for the learning tool.

Will Miller
Political Science,
University of Arkansas
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Newsgroups: bit.listserv.edstat-l
Date:         Wed, 7 Oct 1992 19:46:18 EDT
Reply-To:     Steven R Brown <SBROWN@KENTVM.BITNET>
From:         Steven R Brown <SBROWN@KENTVM.BITNET>
Subject:      Re: FACTOR ANALYSIS AND QUANTUM PHYSICS
              7 Oct 1992 21:06:24 GMT from <mfdjh@UXA.ECN.BGU.EDU>

On Wed, 7 Oct 1992 21:06:24 GMT Dale Hample said:
>I've been reading the thread about Burt/Stephenson/quantum physics with
>much interest, perhaps because it all parallels some references I've
>been looking at which connect Kurt Lewin's field theory with quantum
>physics....
>
Lewin's driving and restraining forces have a Newtonian ring, and so I'd
be somewhat surprised if his ideas fit easily alongside quantum ones --
Einsteinian perhaps, but probably not Bohrian.  Still, his paper on
Aristotelian and Galilean thought (_Journal of General Psychology_ 1931)
is first rate.

>My reason for posting, though, is to wonder if anyone has written a flat
>out history of factor analyis that connects it (& related statistical
>topics) to physics and other elements of the intellectual context in
>which the stats were developed.  I had in mind a book length ms, rather
>than just a series of articles.
>
I very much doubt that there is a full-blown history of factor analysis
and physics.  Leslie Hearnshaw's biography of _Cyril Burt, Psychologist_
(London: Hodder and Stoughton, 1979) indicates that Burt was quite ahead
of his time in delving into quantum theory (p. 304), and that such a
science could not go forward because of the lack of empirical studies to
support it.  The pertinence of Stephenson, as both a physicist and a
psychologist, is that he has provided the means as well as the theoretical
justification for such studies.  There may be other factor-analytic
applications outside the human sciences, but the only one of which I am
aware is Edmund R. Malinowski and Darryl G. Hower's _Factor Analysis in
Chemistry_ (New York: Wiley, 1980), in which the authors try to connect
factor-analytic mathematics to certain quantum properties, but without
much success so far as I could tell.
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Newsgroups: bit.listserv.edstat-l
Date:         Mon, 12 Oct 1992 18:53:09 EDT
Reply-To:     Walt Pirie <WLTPIRIE@VTVM1.BITNET>
From:         Walt Pirie <WLTPIRIE@VTVM1.BITNET>
Subject:      Comportment

Hey out there. If a problem occurs on the net, let's not jump to trash the syso
p the first time it occurs, before we even know if it is his fault.
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Date:         Mon, 12 Oct 1992 09:04:56 +0200
Reply-To:     BOKKIE@UCTVAX.UCT.AC.ZA
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From:         BOKKIE@UCTVAX.UCT.AC.ZA
Subject:      Textbooks

I recommend Howell, D.C. (1989) _Fundamental statistics for the
behavioral sciences_  or the more advanced book by Howell (1992)
_Statistical methods for psychology_ (3rd ed).  There is also
Bryman, A. & Cramer, D. (1990) _Quantitative data analysis for
social scientists_ which is more like a guide to using SPSS than
an introduction to statistics.  As I don't use SPSS, I can't
comment on the worth of this book, though.

Frank Bokhorst
Psychology Department
University of Cape Town
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Newsgroups: bit.listserv.edstat-l
Date:         Mon, 12 Oct 1992 10:31:00 PDT
Reply-To:     Albyn Jones <jones@REED.EDU>
From:         Albyn Jones <jones@REED.EDU>
Subject:      esoterica, again

The List server bounced this posting, claiming redundancy.  I
hope I'm not repeating myself, or anyone else for that matter!

Murray A. Jorgensen [ maj@waikato.ac.nz ]   writes:
>
>
>Like Arnie, I have been having some difficulty appreciating
>all this discussion of the envelope problem. To spend a large
>proportion of class time on explaining the difference between
>various systems of statistical inference seems to me like
>attending to the needs of the instructor, rather than most
>consumers of statistics. Certainly this may be appropriate to
>explore later in the education of a statistical specialist, but
>I don't think that was what most people were talking about.
>
>Isn't _any_ form of interval estimate an interval within
>which it is reasonable to expect the parameter to lie?
>
>Can anyone think of a situation where a user of statistics
>would come to serious harm in thinking that a parameter
>belonged to a particular 95% confidence interval with
>probability .95?

Most of the time in science there is no well specified loss function,
so its hard to compute the damage done by misunderstanding
confidence intervals.  It seems sensible to treat a CI as an estimate
of the  range of plausible values for the parameter, assuming that
the model is correctly specified.  Any more than that seems a bit
optimistic to me.

Lets extend the "who cares what it really means" argument just a bit
farther, to hypothesis tests.  why bother to get it right here either?
After all, the .05 level hypothesis test for \mu = 0 is  just the answer
to the question "is 0 in the 95% CI for \mu?". What's wrong with students
thinking that the p-value is the probability that the null hypothesis is
true?  Why ask them to worry about strange connundrums, such as the
possibility that repeated failures to reject a null hypothesis might
not be strong evidence that the null hypothesis is true?

Surely no harm can come from misunderstanding esoterica like this!
Who cares if students understand the logic of inference, so long as they
can churn out CI's and p-values?

albyn jones
jones@reed.edu
From: gdallal@pearl.tufts.edu (Jerry Dallal)
Newsgroups: bit.listserv.edstat-l
Subject: Re: Niceties of inference schools
Date: 12 Oct 92 10:16:00 GMT
Organization: Tufts University - Medford, MA
News-Software: VAX/VMS VNEWS 1.41

In article <1992Oct12.094824.11360@waikato.ac.nz>, maj@waikato.ac.nz writes...
>Can anyone think of a situation where a user of statistics
>would come to serious harm in thinking that a parameter
>belonged to a particular 95% confidence interval with
>probability .95?

Yes. But to keep the things simple, let x1,x2 be iid U(theta-1, theta+1).
It is easy to show (min, max) is a 50% CI for theta.  If you think it's ok
to say that the probability is 50% that theta lies in the interval then you
should be willing to give me even odds and let me choose  whether theta is
inside or outside the interval.  Certainly, you should be willing to let me 
put up $10 to your $1 and let me choose whether theta is inside or outside the
interval.

Great.  I will choose to bet whenever max-min>1.  I will bet on the interval 
and *never lose*.  Confidence interval are not bet worthy.  The same thing can
be done for the usual 95% two-sided CI for population means based on the t 
distribution, with only minor modifications. 

So.  Does the distinction matter?  You bet it does.  
Newsgroups: bit.listserv.edstat-l
From: amead@s.psych.uiuc.edu (Alan Mead)
Subject: meta-analysis, WITHIN subjects
Organization: UIUC Department of Psychology
Date: Wed, 7 Oct 1992 20:47:06 GMT

I am under the impression that most of the the existing procedures for
performing meta-analyses assume two IDD groups (control and
experimental)?

I have means and standard deviations from the same individuals taking
two forms (paper-and-pencil and computerized) of several tests and I'd
like to answer the question, Does the computerization affect their
scores?

Does anyone have a reference for procedures appropriate to
within-subjects designs?  I have looked at Hedges and Olkins' book, but
their gain-score procedure isn't applicable (my means aren't gain
scores).

Thanks very much.

-alan mead
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Newsgroups: bit.listserv.edstat-l
Date:         Sun, 11 Oct 1992 18:38:00 PDT
Reply-To:     "Peter A. Lachenbruch" <IARSPAL@UCLAMVS.BITNET>
From:         "Peter A. Lachenbruch" <IARSPAL@UCLAMVS.BITNET>
Subject:      textbooks

On the subject of textbooks:
I am teaching a course using Armitage and Berry "Statistical Methods for
Medical Statistics" (or fairly close to that title). I like it, but it may
be at too high a level for the beginning non-math student.
I have been using the new Moore and McCabe book - the second edition - for
some supplementary ideas for me (not for the students). I steal shamelessly
from it - it's the right level and fits in very nicely for beginning students.
A third text is by Ott (again I must apologize for not having exact titles).
We use this book in our general statistics introduction and it seems to be
accepted as well as can be expected by graduate students who really would
prefer to be ABASC ("anywhere but a statistics class").
I heartily second the idea of dropping the computing formulas: either the stu-
dents will use a computer, or the hand calculator will probably compute the
standard deviation for them. This is NOT a good idea for stats majors, as they
may need to know the dangers of bad numerical accuracy someday soon.
Regards - Tony
From: gilpin@iscsvax.uni.edu
Newsgroups: bit.listserv.edstat-l
Subject: Re: physics problems (and posting length)
Date: 9 Oct 92 08:16:54 -0500
Organization: University of Northern Iowa

...
>    I'm all in favor of keeping things as brief as possible, but let's keep
> the censorship of ideas off this list!  as long as the topic in any way per-
> tains to teaching stat-related content, it's fair game.  hit the "delete"
> key if you don't want to read it.
> 
> r. j. harvey
> psychology
> virginia tech

   I share this point of view.  So long as there's obvious interest in a topic,
who cares if it's not universal (incidentally, I wasn't involved in the physics
discussion)?  However, courtesy and efficiency do dictate several desiderata:

1.  Choose an appropriate description in the first place (remember, most
people responding to it will use the "RE: xxx" format).
2.  Avoid quotation of lengthy passages from previous postings.
3.  Consider use of e-mail if a dialogue seems to involve only a few interested
parties.

  Incidentally, I seem to be less distressed by this issue since I started
following most conferences on NEWS rather than by direct subscription--that way
it's not my disk space that's being "wasted".  Unfortunately, that option isn't
always available.
--------
Andy Gilpin, Dept. of Psychology,     |Internet: gilpin@uni.edu
Univ. of Northern Iowa, Cedar Falls,  |Phone: (319) 273-6104
Iowa 50614-0505                       |
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Posted-Date: Fri, 9 Oct 92 09:27:59 EDT
Newsgroups: bit.listserv.edstat-l
Date:         Fri, 9 Oct 1992 09:27:59 EDT
Reply-To:     Tim Arnold <arnold@STAT.NCSU.EDU>
From:         Tim Arnold <arnold@STAT.NCSU.EDU>
Subject:      physics/new lists, thought police

Thanks to Tony Lachenbruch on his message concerning voluntary limits
on message length.  Many of the subscribers to this list have very
small disk space quotas and their "mailbox" is not large enough to
hold even one message as long as the Larsonian physics message.

Thanks to Steven Salbod for pointing out that the (long) physics
message was the exception rather than the rule.

I agree with R. J. Harvey who points out that we don't need thought
police on the list--however, I don't think anyone is campaigning
for that position.

Thanks to David Stretch who correctly points out that (1) the physics
message was a bulk posting and (2) that McElwaine is not a subscriber
to EdStat-L.  (I will probably modify the list settings so that only
subscribers can post to the list in the future--if you have an opinion
on this, please let me know).

To Kirk Steinhorst and Glen McPherson, good luck in the endeavor to
create a new list--I am not sure what the real difference will be
from EdStat-L, but if it helps I'm all for it.  If I can lend
any assistance to the effort, please let me know.

Finally, I'd just like to say that lately there has been a large
amount of traffic on the list, which is good since that's why it was
created in the first place.  From what I've seen on the net we have
one of the best unmoderated lists going.  I am not everybody--I do not
speak for all the members of this list--if anyone has suggestions for
improvement of EdStat-L, please let me know.  We all want harmony,
right?

I close this message by including part of the sign-on message new
subscribers receive:
---------------------------------------------------------------------------
  The following  guidelines have  been agreed  upon by  the membership  of this
list, and it is hoped that you will respect them:

    1) Postings should be directed to  more than one person; messages which are
       clearly of  value to  only one (or  just a few)  members should  be sent
       privately.

    2) No individual should post more than twice per topic in a 24-hour period.

    3)  Postings should  contain the  real name  of the  sender, either  in the
       header or the body of the message.

    4) Personal attacks and insults are prohibited.

---------------------------------------------------------------------------
Thanks for listening,
Tim Arnold
----------------------------------------------------------------------
Tim Arnold                      Instructional Computing
Internet: arnold@stat.ncsu.edu  North Carolina State Univ.
BITNET  : ARNOLD@NCSUSTAT       Dept. of Statistics, Raleigh NC 27695
Phone   : 919 515 2584          FAX: 919 515 7591
----------------------------------------------------------------------
From: dick_darlington@QMRELAY.MAIL.CORNELL.EDU (dick darlington)
Newsgroups: bit.listserv.edstat-l
Subject: Prob statements about CI's
Date: 13 Oct 92 06:25:52 GMT
Reply-To: dick darlington <dick_darlington@QMRELAY.MAIL.CORNELL.EDU>
Comments: Gated by NETNEWS@AUVM.AMERICAN.EDU


                                                                     4:07 AM
  OFFICE MEMO                                                 Time:
                      Subject:
                      Prob statements about CI's                    10-04-92
                                                              Date:

A question has been raised about how we can best explain to our students why
it's a serious error to say "The probability is .95 that the true value lies
within this confidence band."  I'll give 3 answers.
    1. Suppose we once did an exhaustive count of the number of broken widgets
among the good widgets in a warehouse, and found 80 broken ones.  We know
widgets break spontaneously but never repair themselves spontaneously.  Now we
draw a sample, and standard confidence interval procedures lead us to say "The
probability is .95 that the number of broken widgets is between 65 and 75."
Clearly that doesn't make sense; we know it's 80 or over.
    2. Two investigators draw random samples from the same population and each
derives a confidence interval for the true mean.  However, the confidence
intervals don't overlap.  Surely we wouldn't want to say "the probability is
.95" that the true mean is within each interval.
    3. The most common (and thus the most important) case is less clear-cut
than these odd examples.  If you have 20 means in a one-way analysis of
variance, and you select post hoc the cell with the highest mean, surely you
wouldn't want to say "the probability is .95" that the true cell mean is within
a standard confidence band around the observed mean.  The fact that this mean
was selected post hoc as the highest one is surely relevant.  A similar
argument applies to the highest correlation selected from a correlation matrix,
and is why Systat doesn't print significance levels under each correlation in a
matrix--they have no meaning when selected post hoc from a broader set.
   What all these cases have in common is that you know something else about
the situation than what you have used to construct the confidence band.  My own
opinion is that they all illustrate the need for some kind of Bayesian or
quasi-Bayesian approach in order to make good intuitive sense.
Dick Darlington, Psychology, Cornell
#000#
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