closed, winter break. no chance to see it this year.
On 25 Dec 2001, Donald Burrill wrote:
> On Tue, 11 Dec 2001, Vadim and Oxana Marmer wrote:
>
> > besides, who needs those tables? we have computers now, don't we?
> > I was told that there were tables for logarithms once. I have not seen
> > o
On Tue, 11 Dec 2001, Vadim and Oxana Marmer wrote:
> besides, who needs those tables? we have computers now, don't we?
> I was told that there were tables for logarithms once. I have not seen
> one in my life. Is not it the same kind of stuff?
If you _want_ to see one, you have no farther to go
>
> Sigma is hardly ever known, so you must use t. Then why not simply tell
> the students: "use the t table as far as it goes, (usually around
> n=120), and after that, use the n=\infty line (which corresponds to the
> normal distribution). Then there is no need for a rule for "when to use
> z, w
> 3) When n is greater than 30 and we do not know sigma, we must estimate
> sigma using s so we really should be using t rather than z.
you are wrong. you use t-distribution not because you don't know sigma,
but because your statistic has EXACT t-distribution under certain
conditions. I know tha
besides, who needs those tables? we have computers now, don't we?
I was told that there were tables for logarithms once. I have not seen one
in my life. Is not it the same kind of stuff?
>
> 3. Outdated.
>
> on the grounds that when sigma is unknown, the proper distribution is t
> (unless N is
On Mon, 10 Dec 2001 12:57:29 -0400, Gus Gassmann
<[EMAIL PROTECTED]> wrote:
> Art Kendall wrote:
>
> (putting below the previous quotes for readability)
>
> > Gus Gassmann wrote:
> >
> > > Dennis Roberts wrote:
> > >
> > > > this is pure speculation ... i have yet to hear of any convincing case
At 03:42 PM 12/10/01 +, Jerry Dallal wrote:
>Dennis Roberts wrote:
>
> > this is pure speculation ... i have yet to hear of any convincing case
> > where the variance is known but, the mean is not
>
>A scale (weighing device) with known precision.
as far as i know ... knowing the precision is
Jon Cryer wrote:
> But then you should use a binomial (or hypergeometric) distribution.
>
> Jon Cryer
>
> p.s. Of course, you might approximate by an appropriate normal
> distribution.
Quite, and then you are in a situation where you know (or at least
pretend to know)
the population variance, t
Only as an approximation.
At 12:57 PM 12/10/01 -0400, you wrote:
>Art Kendall wrote:
>
>(putting below the previous quotes for readability)
>
> > Gus Gassmann wrote:
> >
> > > Dennis Roberts wrote:
> > >
> > > > this is pure speculation ... i have yet to hear of any convincing case
> > > > where
Usually I would use software. As I tried to show is the sample syntax I posted
earlier, it doesn't usually make much difference whether you use z or t.
Gus Gassmann wrote:
> Art Kendall wrote:
>
> (putting below the previous quotes for readability)
>
> > Gus Gassmann wrote:
> >
> > > Dennis Rob
Art Kendall wrote:
(putting below the previous quotes for readability)
> Gus Gassmann wrote:
>
> > Dennis Roberts wrote:
> >
> > > this is pure speculation ... i have yet to hear of any convincing case
> > > where the variance is known but, the mean is not
> >
> > What about that other applicati
the sample mean of the dichotomous (one_zero, dummy) variable is known, It
is the proportion.
Gus Gassmann wrote:
> Dennis Roberts wrote:
>
> > this is pure speculation ... i have yet to hear of any convincing case
> > where the variance is known but, the mean is not
>
> What about that other ap
I always thought that the precision of a scale was
proportional
to the amount weighed. So don't you have to know the mean
before you
know the standard deviation? But wait a minute - we are trying
assess
the size of the mean!
Jon Cryer
At 03:42 PM 12/10/01 +, you wrote:
Dennis Roberts wrote:
>
Dennis Roberts wrote:
> this is pure speculation ... i have yet to hear of any convincing case
> where the variance is known but, the mean is not
A scale (weighing device) with known precision.
=
Instructions for joining and leavi
But then you should use a binomial (or hypergeometric)
distribution.
Jon Cryer
p.s. Of course, you might approximate
by an appropriate normal distribution.
At 11:39 AM 12/10/01 -0400, you wrote:
Dennis Roberts wrote:
> this is pure speculation ... i have yet to hear of any convincing
case
> where
Dennis Roberts wrote:
> this is pure speculation ... i have yet to hear of any convincing case
> where the variance is known but, the mean is not
What about that other application used so prominently in texts of
business statistics, testing for a proportion?
At 04:14 AM 12/10/01 +, Jim Snow wrote:
>"Ronny Richardson" <[EMAIL PROTECTED]> wrote in message
>[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
>
> > A few weeks ago, I posted a message about when to use t and when to use z.
>
>I did not see the earlier postings, so forgive me if I repeat advic
Ronny Richardson wrote:
>
> Are they
>
> 1. Wrong
> 2. Just oversimplifying it without telling the reader
Neither, really. The MAIN objection to "z over 30" is that it adds an
an unnecessary step to the decision process. If it actually simplified
things greatly I reckon we could live
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If your conclusion differs whether you use t or z, your decision is "at
the
edge".
The total uncertainty (T) in a decision has two part
Ronny Richardson wrote:
>
> A few weeks ago, I posted a message about when to use t and when to use z.
> In reviewing the responses, it seems to me that I did a poor job of
> explaining my question/concern so I am going to try again.
>
> I have included a few references this time since one res
[EMAIL PROTECTED] (Ronny Richardson) wrote in message
news:<[EMAIL PROTECTED]>...
> A few weeks ago, I posted a message about when to use t and when to use z.
> In reviewing the responses, it seems to me that I did a poor job of
> explaining my question/concern so I am going to try again.
>
> I
"Ronny Richardson" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> A few weeks ago, I posted a message about when to use t and when to use z.
I did not see the earlier postings, so forgive me if I repeat advice already
given.:-)
1. The consequences of usi
On Sun, 9 Dec 2001, Ronny Richardson wrote in part:
> Bluman has a figure (2, page 333) that is supposed to show the student
> "When to Use the z or t Distribution." I have seen a similar figure in
> several different textbooks.
So have I, sometimes as a diagram or flow chart, sometimes in par
A few weeks ago, I posted a message about when to use t and when to use z.
In reviewing the responses, it seems to me that I did a poor job of
explaining my question/concern so I am going to try again.
I have included a few references this time since one responder doubted the
items to which I was
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