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necessary theoretical 'scaffolding' or 'superceded procedures', and what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 in a
Date: Fri, 20 Apr 2001 13:02:57 -0500
From: Jon Cryer [EMAIL PROTECTED]
Could you please give us an example of such a situation?
Consider first a set of measurements taken with
a measuring instrument whose sampling errors have a known standard
deviation (and approximately normal
These examples come the closest I have seen to having a known variance.
However, often measuring instruments, such as micrometers, quote their
accuracy as a percentage of the size of the measurement. Thus, if you
don't know the mean you also don't know the variance.
Jon Cryer
At 09:28 AM
At 1:18 PM -0500 23/4/01, Jon Cryer wrote:
These examples come the closest I have seen to having a known variance.
However, often measuring instruments, such as micrometers, quote their
accuracy as a percentage of the size of the measurement. Thus, if you
don't know the mean you also don't know
Jon Cryer wrote:
These examples come the closest I have seen to having a known variance.
However, often measuring instruments, such as micrometers, quote their
accuracy as a percentage of the size of the measurement. Thus, if you
don't know the mean you also don't know the variance.
the fundamental issue here is ... is it reasonably to expect ... that when
you are making some inference about a population mean ... that you will
KNOW the variance in the population?
i suspect that the answer is no ... in all but the most convoluted cases
... or, to say it another way ...
dennis roberts wrote:
the fundamental issue here is ... is it reasonably to expect ... that when
you are making some inference about a population mean ... that you will
KNOW the variance in the population?
No, Dennis, of course it isn't - at least in the social sciences and
I can't help but be reminded of learning to ride a bicycle. 99.% of
people ride one with two wheels (natch!) - but many children do start to
learn with training wheels..
Alan
dennis roberts wrote:
the fundamental issue here is ... is it reasonably to expect ... that when
you are
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 how to
Alan:
Could you please give us an example of such a situation?
"Consider first a set of measurements taken with
a measuring instrument whose sampling errors have a known standard
deviation (and approximately normal distribution)."
Jon
At 01:10 PM 4/20/01 -0400, you wrote:
(This note is
Alan:
I don't understand your comments about the estimation of a proportion.
It sounds to me as if you are using the estimated standard error. (Surely
you are not assuming a known standard error.) You are presumably, also
using the normal approximation to the binomial (or perhaps the
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
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, is
However, rather than do that why not right on to F? Why do t at all when you can do anything with F that t can do plus a whole lot more?
At 10:58 PM 4/19/01 -0400, you wrote:
>students have enough problems with all the stuff in stat as it is ... but,
>when we start some discussion about sampling
At 10:39 AM 4/19/01 -0500, Paul Swank wrote:
However, rather than do that why not right on to F? Why do t at all when
you can do anything with F that t can do plus a whole lot more?
don't necessarily disagree with this but, i don't ever see in the
literature in two group situations comparing
Paul Swank wrote:
However, rather than do that why not right on to F? Why do t at all when you can do
anything with F that t can do plus a whole lot more?
Because the mean, normalized using the hypothesized mean and the
observed standard deviation, has a t distribution and not an F
I agree. I still teach the t test also because of this, but at the same time I realize that what goes around, comes around, so what we are doing is ensuring that we will continue to see t tests in the literature. However, I find linear models easier to teach (once I erase the old stuff from their
They are more than just related. One is a natural extension of the other just as chi-square is a natural extension of Z. With linear models, one can begin with a simple one sample model and build up to multiple factors and covariates using the same basic framework, which I find easier to make
I agree. I normally start inference by using the binomial and then then the normal approximation to the binomial for large n. It might be best to begin all graduate students with nonparametric statistics followed by linear models. Then we could get them to where they can do something interesting
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 students
I
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 ... the
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
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.
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
"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
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 excellent btw).
Perhaps someone would be kind enough to cl
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
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, since it
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