On 24 Apr 2001, Mark W. Humphries wrote:
>> I concur. As I mentioned at the start of this thread, I am
"self-learning"
>> statistics from books. I have difficulty telling what is being taught as
>> necessary theoretical 'scaffolding' or 'superceded procedures', and what
one
>> would actually apply
dennis roberts wrote:
> start with the realistic case ... even if it takes a bit more "doing" to
> explain it
Depends what you're trying to teach. If mathematical statistics, I
wouldn't think of starting with a t. If data analysis, I wouldn't
think of starting with a z. As a read through some
In article <[EMAIL PROTECTED]>,
dennis roberts <[EMAIL PROTECTED]> wrote:
>this is why i personally don't like to start with the case where you assume
>that you know sigma ... as a "simplification" ... since it is totally
>unrealistic
>
>start with the realistic case ... even if it takes a bit
Dennis
How many actual times do you meet with the class during the course of one
term? I know that when I taught we had the undergraduate students meet for
1-1/2 hours for from 21 to 30 sessions depending on the department. In
graduate school we met with the students for 2 hours per class fo
At 05:15 PM 4/22/01 -0400, Rich Ulrich wrote:
>On 21 Apr 2001 13:04:55 -0700, [EMAIL PROTECTED] (Will Hopkins)
>wrote:
>
>So you guys are all giving advice about teaching statistics to
>psychology majors/ graduates, who have no aspirations or
>potential for being anything more than "consumers" (re
On 21 Apr 2001 13:04:55 -0700, [EMAIL PROTECTED] (Will Hopkins)
wrote:
> I've joined this one at the fag end. I'm with Dennis Roberts. The way I
> would put it is this: the PRINCIPLE of a sampling distribution is actually
> incredibly simple: keep repeating the study and this is the sort of
Hi
On Fri, 20 Apr 2001, dennis roberts wrote:
> At 10:58 AM 4/20/01 -0500, jim clark wrote:
> > What does a t-distribution mean to a student who does not
> >know what a binomial distribution is and how to calculate the
> >probabilities, and who does not know what a normal distribution
> >is and
I've joined this one at the fag end. I'm with Dennis Roberts. The way I
would put it is this: the PRINCIPLE of a sampling distribution is actually
incredibly simple: keep repeating the study and this is the sort of spread
you get for the statistic you're interested in. What makes it incredi
At 10:58 AM 4/20/01 -0500, jim clark wrote:
> What does a t-distribution mean to a student who does not
>know what a binomial distribution is and how to calculate the
>probabilities, and who does not know what a normal distribution
>is and how to obtain the probabilities?
good question but, NO
Jim, Dennis, list at large
I like Jim's rationale for introducing the binomial first rather than the
normal or t. I may try it next semester (too late this semester). He much
more eloquently explained why we may not wish to jump straight to the
t-test than I did.
Chris
At 10:58 AM 04/20/200
Hi
It has been a few years since teaching intro stats to psych
students, but I too liked the sequence: binomial -> normal ->
t-distribution ...
The binomial allows students with basic probability skills to
actually calculate the probabilities for a sampling distribution.
This provides a solid
I don't believe anyone has bothered to define what they mean by a z-test.
There are two issues that must be dealt with: (1), What statistic is to be
used
and (2), what distribution is to be used to assess the size of that statistic.
I contend that a z "statistic," viz., (Ybar-mu0)/(sigma/sqrt(n))
nice note mike
>Impossible? No. Requiring a great deal of effort on the part of some
>cluster of folks? Definitely!
absolutely!
>There is some discussion of this very possibility in Psychology, although
>I've yet to see evidence of fruition. A very large part of the problem,
>in my mind,
On Fri, 20 Apr 2001, dennis roberts wrote:
>
> what i would like to see .. which is probably impossible in general (and
> has been discussed before) ... it a more integrated approach to data
> collection ... WITHIN THE SAME COURSE OR A SEQUENCE OF COURSES ... so that
> when you get to the ana
alan and others ...
perhaps what my overall concern is ... and others have expressed this from
time to time in varying ways ... is that
1. we tend to teach stat in a vacuum ...
2. and this is not good
the problem this creates is a disconnect from the question development
phase, the measure de
I wrote, suggesting that forthose with a little learning the Z test is a
dangerous thing,
and Rich Ulrich responded:
> Mainly, I disagree.
>
> I had read 3 or 4 statistic books and used several stat programs
> before I enrolled in graduate courses. One of the *big surprises* to
> me was to l
All of your observations about the deficiencies of data are perfectly
valid. But what do you do? Just give up because your data are messy, and
your assumptions are doubtful and all that? Go and dig ditches instead?
You can only analyse data by making assumptions - by working with models
of the wor
At 08:46 AM 4/20/01 +1000, Alan McLean wrote:
>So the two good reasons are - that the z test is the basis for the t,
>and the understanding that knowledge has a very direct value.
>
>I hasten to add that 'knowledge' here is always understood to be
>'assumed knowledge' - as it always is in statist
There is at least two very good pedagogical reasons for teaching z
tests. Both the z and t tests are based on normality - the t test is
used only because the model standard deviation is unknown or rather,
there is no assumed value for it. Whether or not this is in practice
'always' the case is irr
On 19 Apr 2001 05:26:25 -0700, [EMAIL PROTECTED] (Robert J.
MacG. Dawson) wrote:
[ ... ]
> The z test and interval do have some value as a pedagogical
> scaffold with the better students who are intended to actually
> _understand_ the t test at a mathematical level by the end of the
> c
At 04:42 PM 4/19/01 +, Radford Neal wrote:
>In article <[EMAIL PROTECTED]>,
>dennis roberts <[EMAIL PROTECTED]> wrote:
>
>I don't find this persuasive.
nor the reverse ... since we have NO data on any of this ... only our own
notions of how it MIGHT play itself out inside the heads of studen
Why not introduce hypothesis testing in a binomial setting where there are
no nuisance parameters and p-values, power, alpha, beta,... may be obtained
easily and exactly from the Binomial distribution?
Jon Cryer
At 01:48 AM 4/20/01 -0400, you wrote:
>At 11:47 AM 4/19/01 -0500, Christopher J. Mec
At 11:47 AM 4/19/01 -0500, Christopher J. Mecklin wrote:
>As a reply to Dennis' comments:
>
>If we deleted the z-test and went right to t-test, I believe that
>students' understanding of p-value would be even worse...
i don't follow the logic here ... are you saying that instead of their
under
In article <[EMAIL PROTECTED]>,
dennis roberts <[EMAIL PROTECTED]> wrote:
>students have enough problems with all the stuff in stat as it is ... but,
>when we start some discussion about sampling error of means ... for use in
>building a confidence interval and/or testing some hypothesis ... th
As a reply to Dennis' comments:
I wage the same fight in my head each semester about this time, when I'm
introducing hypo. testing to students in my undergrad intro to stats
class. I teach out of Moore and McCabe.
It seems to me that a possible justification for introducing CIs and
hypothesi
students have enough problems with all the stuff in stat as it is ... but,
when we start some discussion about sampling error of means ... for use in
building a confidence interval and/or testing some hypothesis ... the first
thing observant students will ask when you say to them ...
assume SR
: You're running into a historical artifact: in pre-computer days, using the
: normal distribution rather than the t distribution reduced the size of the
: tables you had to work with. Nowadays, a computer can compute a t
: probability just as easily as a z probability, so unless you're in the
vant
ones.
Cheers,
Mark
-Original Message-
From: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED]]On Behalf Of Eric Bohlman
Sent: Tuesday, April 17, 2001 4:44 AM
To: [EMAIL PROTECTED]
Subject: Re: Student's t vs. z tests
Mark W. Humphries <[EMAIL PROTECTED]> wrote:
> Hi,
> I am a
Sent: Monday, April 16, 2001 3:43 PM
Subject: Re: Student's t vs. z tests
> Mark W. Humphries <[EMAIL PROTECTED]> wrote:
> > Hi,
>
> > I am attempting to self-study basic multivariate
statistics using Kachigan's
> > "Statistical Analysis" (which I find
"Mark W. Humphries" wrote:
> If I understand correctly the t test, since it takes into account degrees of
> freedom, is applicable whatever the sample size might be, and has no
> drawbacks that I could find compared to the z test. Have I misunderstood
> something?
>From my class notes (which, in
Mark W. Humphries <[EMAIL PROTECTED]> wrote:
> Hi,
> I am attempting to self-study basic multivariate statistics using Kachigan's
> "Statistical Analysis" (which I find excellent btw).
> Perhaps someone would be kind enough to clarify a point for me:
> If I understand correctly the t test, sinc
If you knew the population SD (not likely if you are estimating the
population mean), you would have more power with the z statistic (which
requires that you know the population SD rather than estimating it from the
sample) than with t.
-Original Message-
If I understand correctly the t t
32 matches
Mail list logo
