Re: chi square validity?

[Glen]

[EMAIL PROTECTED] (Benjamin Kenward) wrote in message 
news:<9vnj9m$s2c$[EMAIL PROTECTED]>...
> Hi folks,
> 
> Let's say you have a repeatable experiment and each time the result can be
> classed into a number of discrete categories (in this real case, seven).
> If a treatment has no effect, it is known what the expected by chance
> distribution of results between these categories would be. I know that a
> good test to see if a distribution of results from a particular treatment
> is different to the expected by chance distribution is to use a
> chi-squared test. What I want to know is, is it valid to compare just one
> category? In other words, for both the obtained and expected
> distributions, summarise them to two categories, one of which is the
> category you are interested in, and the other containing all the other
> categories. If the chi-square result of the comparison of these categories
> is significant, can you say that your treatment produces significantly
> more results in particularly that category, or can you only think of the
> whole distribution?

Yes, as long as the choice of which category to do it for is not based
on the data... no fair just testing the most extreme one.

Glen

Glen


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Re: How ro perform "Runs Test"??

[Glen]

[EMAIL PROTECTED] (Chia C Chong) wrote in message 
news:<[EMAIL PROTECTED]>...
> I am using nonlinear regression method to find the best parameters for
> my data. I came across a term called "runs test" from the Internet. It
> mentioned that this is to determines whether my data is differ
> significantly from the equation model I select for the nonlinear
> regression. Can someone please let me know how should I perform the
> run tests??

You need to use a runs test that's adjusted for the dependence in the
residuals. The usual runs test in the texts won't apply.

Glen


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Re: Standardizing evaluation scores

[Jay Warner]

A classic problem of 'norming' or 'standardizing' the scale and the
preceptors.  Can you find a couple students who fall near the bottom and
tops of the scale?  Preferably ones whose final rankings are not 'permanent
record'?

then you would have each preceptor use these two students as 'baseline'
indicators of what a 2 means, and what an 8 means.  then have each person do
the regular ranking of students, using these as your indicators.

It might be possible for the attendant group of preceptors to agree on the
ranking of a pair of students, in each specialty or area.  then use these
for ranking within that specialty.

Failing this kind of development for mutual agreement, you might be able to
describe a 2 or 3 rating, and a 7 or 8 rating, in such a way that
generalized agreement would be obtained, and each grade would be set in
comparison to this descriptive scale.  This is essentially what the Baldrige
Criteria does, for industrial/ educational/ health care operations.

Of course, if it's grades we are discussing, it is entirely likely that
virtually nobody gets grades in certain ranges, such as the equivalent of C
or below on an A- F scale.  If Harvard can graduate over half a class as Cum
Laude, the rest of us can skew grades anywhere we like.

Jay

Doug Federman wrote:

> I have a dilemma which I haven't found a good solution for.  I work with
> students who rotate with different preceptors on a monthly basis.  A
> student will have at least 12 evaluations over a year's time.  A
> preceptor usually will evaluate several students over the same year.
> Unfortunately, the preceptors rarely agree on the grades.  One preceptor
> is biased towards the middle of the 1-9 likert scale and another may be
> biased towards the upper end.  Rarely, does a given preceptor use the 1-9
> range completely.  I suspect that a 6 from an "easy" grader is equivalent
> to a 3 from a "tough" grader.
>
> I have considered using ranks to give a better evaluation for a given
> student, but I have a serious constraint.  At the end of each year, I
> must submit to another body their evaluation on the original 1-9 scale,
> which is lost when using ranks.
>
> Any suggestions?
>
> --
> "It has often been remarked that an educated man has probably forgotten
> most of the facts he acquired in school and university. Education is what
> survives when what has been learned has been forgotten."
> - B.F. Skinner New Scientist, 31 May 1964, p. 484
>
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--
Jay Warner
Principal Scientist
Warner Consulting, Inc.
 North Green Bay Road
Racine, WI 53404-1216
USA

Ph: (262) 634-9100
FAX: (262) 681-1133
email: [EMAIL PROTECTED]
web: http://www.a2q.com

The A2Q Method (tm) -- What do you want to improve today?






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s-function in SPSS curve estimation

[Johannes Hartig]

Hi all,
Does anyone know the original applications
or the "meaning" of the "S"-function in SPSS?
I know the function itself:
Y = e**(b0 + (b1/t)) or
ln(Y) = b0 + (b1/t)
and I know how the curve looks like, but I am
wondering in which fields of research this function
is typically used and which empirical relations it
describes?
Thanks for any hint,
Johannes




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Re: What does these mean in statistical sense??

[Chia C Chong]

Thanks for all the helpful suggestions...

Cheers,
CCC

"Art Kendall" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> try doing a scattergram of your two variables.  It should look much more
like a
> cloud than a line.
>
> "Anon." wrote:
>
> > Chia C Chong wrote:
> > >
> > > I have 2 random variables (X and Y). The covariance,c was found equal
to
> > > 20.2006 and their correlation coefficient,p was 0.0245.
> > >
> > > From the statistical book, if their c=0, means that X and Y are
uncorrelated
> > > i.e p=0. However, in my case, c is quite large but p is extremely
> > > small...So, what justification could I said with this kind of data??
> > >
> > It measn the variances are large.  If s_A is the standard deviation of
> > A, then
> >
> > p_XY = c_XY/(s_X*s_Y)
> >
> > So for your data, s_X*s_Y = 824.5.  This is why we use p, it's re-scaled
> > so that the variances are 1, so we can compare correlations of variables
> > with different variances.  In this case, p looks very close to 0.
> >
> > Bob
> >
> > --
> > Bob O'Hara
> > Metapopulation Research Group
> > Division of Population Biology
> > Department of Ecology and Systematics
> > PO Box 17 (Arkadiankatu 7)
> > FIN-00014 University of Helsinki
> > Finland
> >
> > tel: +358 9 191 28779  mobile: +358 50 599 0540
> > (Yes, I have finally joined 21st Century Finland)
> > fax: +358 9 191 28701email: [EMAIL PROTECTED]
> > To induce catatonia, visit 
> >
> > It is being said of a certain poet, that though he tortures the English
> > language, he has still never yet succeeded in forcing it to reveal his
> > meaning
> > - Beachcomber
>




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Re: What does these mean in statistical sense??

[Art Kendall]

This is a multi-part message in MIME format.
--D8246F46A01791942B12542B
Content-Type: text/plain; charset=us-ascii
Content-Transfer-Encoding: 7bit

try doing a scattergram of your two variables.  It should look much more like a
cloud than a line.

"Anon." wrote:

> Chia C Chong wrote:
> >
> > I have 2 random variables (X and Y). The covariance,c was found equal to
> > 20.2006 and their correlation coefficient,p was 0.0245.
> >
> > From the statistical book, if their c=0, means that X and Y are uncorrelated
> > i.e p=0. However, in my case, c is quite large but p is extremely
> > small...So, what justification could I said with this kind of data??
> >
> It measn the variances are large.  If s_A is the standard deviation of
> A, then
>
> p_XY = c_XY/(s_X*s_Y)
>
> So for your data, s_X*s_Y = 824.5.  This is why we use p, it's re-scaled
> so that the variances are 1, so we can compare correlations of variables
> with different variances.  In this case, p looks very close to 0.
>
> Bob
>
> --
> Bob O'Hara
> Metapopulation Research Group
> Division of Population Biology
> Department of Ecology and Systematics
> PO Box 17 (Arkadiankatu 7)
> FIN-00014 University of Helsinki
> Finland
>
> tel: +358 9 191 28779  mobile: +358 50 599 0540
> (Yes, I have finally joined 21st Century Finland)
> fax: +358 9 191 28701email: [EMAIL PROTECTED]
> To induce catatonia, visit 
>
> It is being said of a certain poet, that though he tortures the English
> language, he has still never yet succeeded in forcing it to reveal his
> meaning
> - Beachcomber

--D8246F46A01791942B12542B
Content-Type: text/x-vcard; charset=us-ascii;
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n:Kendall;Art
tel;work:301-864-5570
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Re: What does these mean in statistical sense??

[Anon.]

Chia C Chong wrote:
> 
> I have 2 random variables (X and Y). The covariance,c was found equal to
> 20.2006 and their correlation coefficient,p was 0.0245.
> 
> From the statistical book, if their c=0, means that X and Y are uncorrelated
> i.e p=0. However, in my case, c is quite large but p is extremely
> small...So, what justification could I said with this kind of data??
> 
It measn the variances are large.  If s_A is the standard deviation of
A, then 

p_XY = c_XY/(s_X*s_Y)

So for your data, s_X*s_Y = 824.5.  This is why we use p, it's re-scaled
so that the variances are 1, so we can compare correlations of variables
with different variances.  In this case, p looks very close to 0.

Bob

-- 
Bob O'Hara
Metapopulation Research Group
Division of Population Biology
Department of Ecology and Systematics
PO Box 17 (Arkadiankatu 7)
FIN-00014 University of Helsinki
Finland

tel: +358 9 191 28779  mobile: +358 50 599 0540
(Yes, I have finally joined 21st Century Finland)
fax: +358 9 191 28701email: [EMAIL PROTECTED]
To induce catatonia, visit 

It is being said of a certain poet, that though he tortures the English
language, he has still never yet succeeded in forcing it to reveal his
meaning
- Beachcomber


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Re: claculate L2 for Venus

[Robert J. MacG. Dawson]

Brad Guth wrote:
> 
> My URL has much to do with the discovery of "GUTH Venus"
> http://geocities.com/bradguth
> 
> One of my questions has to deal with a manned mission, which may need
> to utilize the orbit station L2, as an orbit situated so as to sustain
> life onboard the spacecraft for several months to perhaps years.
> 
> If the space craft were to be represented by upwards of 1000 tons
> mass, what would the calculated L2 become?
> 
> The same calculation at 500 tons and perhaps 100 tons.
> 
> I've asked this of many NASA types and they exploded. Please don't
> explode on my account. A good lead to an astro/gravity-calculator may
> do just fine.

*BANG!*

Just kidding. I presume that by "the orbit station L2" you mean the
(unstable) second Lagrange point of the Sol/Venus pair?  

The location of this point is not affected to first order by placing a
mass there. The only effect would be a second-order effect due to the
perturbation, due to the station's mass, of the orbit of Venus [and, if
you want to get truly silly, of the position of the Sun.]

As in this case "order of magnitude" is essentially the ratio of the
mass of the station to that of the Sun [not of Venus, which is the
object being moved...] you can see that the "empty" location of L2 would
continue to be valid in the presence of any object we could put there,
probably to within a micron.

That said, I feel I must add something on the subject of the NASA Venus
images that you think show artifacts. I do not know if you are familiar
with either marquetry or gemmology. If you have any experience with the
first, you will probably know about the American red gum tree
(_Fluidambar_styrax_ - what a beautiful name!). Its veneer is much
sought after by marquetarians, because a slice cutting through both
heartwood and sapwood often contains a detailed desert scene, with
cirrus clouds in the sky and sand dunes on the ground. The dunes are
often even silhouetted against the skyline.
There are also sedimentary rocks that are used for jewellery which,
when sliced, regularly show landscapes in which the eye "recognizes"
many details. Again, I have seen a poster with an entire alphabet made
up of photographs of details from butterflies' wings; and while *some*
resemblances between such markings and other creatures are presumably
evolutionarily advantageous in that the resemblance is to something a
predator will avoid, this hardly explains the sometimes near-perfect
human skull seen on the Death's-Head Moth. [You will have seen it on the
cover of most paperback editions of "The Silence of the Lambs". On some
of these it's retouched, so that the skull itself is made up of several
ghostly female bodies; but the basic image is fairly accurate.]
What I'm getting at is that people tend to underestimate the ability of
naturally-arising phenomena to mimic other things, without intelligent
intervention. You should also be aware that these photographs were not
taken using light, but by radar. If I remember correctly, they were not
even taken as images, but as a linear scan pattern, assembled into an
image by a computer on Earth. The bright lines are NOT
differently-colored regions, or uniformly higher (or lower) than those
around them; they are cliffs between terraces. If you imagine that the
model is on a table top, made of dark clay, and lit from the side, it
will be easier to interpret. Or think of a landscape seen at sunset. 

-Robert Dawson


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What does these mean in statistical sense??

[Chia C Chong]

I have 2 random variables (X and Y). The covariance,c was found equal to
20.2006 and their correlation coefficient,p was 0.0245.

>From the statistical book, if their c=0, means that X and Y are uncorrelated
i.e p=0. However, in my case, c is quite large but p is extremely
small...So, what justification could I said with this kind of data??

Thanks..

CCC






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Re: Maximum Likelihood Question

[David Jones]

"Herman Rubin" <[EMAIL PROTECTED]> wrote in message
9vqoln$[EMAIL PROTECTED]">news:9vqoln$[EMAIL PROTECTED]...
>
> Maximum likelihood is ASYMPTOTICALLY optimal in LARGE
> samples.  It may not be good for small samples; it pays
> to look at how the actual likelihood function behaves.
> The fit is always going to improve with more parameters.
>

This may be the trouble in the actual problem being attempted, but
there are other possibilities, besides the potential for having
programmed things incorrectly. One such trouble might be that the
parameters are constrained and that the maximum-likelihood estimates
given such constraints are falling on the edge of the allowed region
.. then the usual asymptotics don't apply.

David Jones




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