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edstat-digest Tuesday, January 15 2002 Volume 2000 : Number 610
----------------------------------------------------------------------
Date: Mon, 14 Jan 2002 17:19:17 -0500
From: "Stan Brown" <[EMAIL PROTECTED]>
Subject: Re: SAT Question Selection
[cc'd to previous poster; please follow up in newsgroup]
L.C. <[EMAIL PROTECTED]> wrote in sci.stat.edu:
>Back in my day (did we have days back then?) I recall
>talk of test questions on the SAT. That is, these questions
>were not counted; they were being tested for (I presume)
>some sort of statistical validity.
>
>Does anyone have any statistical insight into the SAT question
>selection process. Does anyone have a specific lead? I can
>find virtually nothing.
I remember reading a good book about the inner operation of ETS
(administers the SATs), with some bits about the "test" questions
you refer to, but I can't quite remember the title. I've searched
the catalog of my old library, and this _may_ be it:
Lemann, Nicholas.
The big test : the secret history of the American meritocracy
New York : Farrar, Straus and Giroux, 1999.
- --
Stan Brown, Oak Road Systems, Cortland County, New York, USA
http://oakroadsystems.com/
"What in heaven's name brought you to Casablanca?"
"My health. I came to Casablanca for the waters."
"The waters? What waters? We're in the desert."
"I was misinformed."
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------------------------------
Date: Mon, 14 Jan 2002 19:37:01 -0500
From: Dennis Roberts <[EMAIL PROTECTED]>
Subject: Re: SAT Question Selection
for the SAT ... which is still paper and pencil ... you will find multiple
sections ... math and verbal ... as far as i know ... there usually are 3
of one and 2 of the other ... the one with 3 has A section that is called
"operational" ... which does NOT count ... but is used for trialing new
items ... revised items ... etc.
don't expect them to tell you which one that is however ...
in a sense ... they are making YOU pay for THEIR pilot work ... and, of
course, if you happen to really get fouled up on the section that is
operational and does not count ... it could carry over "emotionally" to
another section ... and have some (maybe not much) impact on your
motivation to do well on that next section
unless it has changed ...
At 05:19 PM 1/14/02 -0500, you wrote:
>[cc'd to previous poster; please follow up in newsgroup]
>
>L.C. <[EMAIL PROTECTED]> wrote in sci.stat.edu:
> >Back in my day (did we have days back then?) I recall
> >talk of test questions on the SAT. That is, these questions
> >were not counted; they were being tested for (I presume)
> >some sort of statistical validity.
> >
> >Does anyone have any statistical insight into the SAT question
> >selection process. Does anyone have a specific lead? I can
> >find virtually nothing.
>
>I remember reading a good book about the inner operation of ETS
>(administers the SATs), with some bits about the "test" questions
>you refer to, but I can't quite remember the title. I've searched
>the catalog of my old library, and this _may_ be it:
>
>Lemann, Nicholas.
> The big test : the secret history of the American meritocracy
> New York : Farrar, Straus and Giroux, 1999.
>
>--
>Stan Brown, Oak Road Systems, Cortland County, New York, USA
> http://oakroadsystems.com/
>"What in heaven's name brought you to Casablanca?"
>"My health. I came to Casablanca for the waters."
>"The waters? What waters? We're in the desert."
>"I was misinformed."
>
>
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>problem of INAPPROPRIATE MESSAGES, and archives are available at
> http://jse.stat.ncsu.edu/
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_________________________________________________________
dennis roberts, educational psychology, penn state university
208 cedar, AC 8148632401, mailto:[EMAIL PROTECTED]
http://roberts.ed.psu.edu/users/droberts/drober~1.htm
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------------------------------
Date: 15 Jan 2002 02:00:48 GMT
From: [EMAIL PROTECTED] (EugeneGall)
Subject: Re: Proportionate vs. disproportionate
Rich Ulrich wrote:
>I am not positive, but
>I think I would have objected to "equal % change"
>as =proportionate= by the time I finished algebra in high school.
>
>I know I have objected to similar confusion, on principled
>grounds, since I learned about Odds Ratios.
>
>I suspect that the original sample was small enough that
>the apparent difference in ORs was not impressive.
>--
>
I too think that the odds ratio is the appropriate way to present the data, but
after looking at these results, I can appreciate why the Gallup organization
didn't do so.
The data on racial favorability ratings which Gallup called 'proportionate' not
'disproportionate':
GWBush favorability pre- and post-9/11
Pre-disaster Post-disaster OddsRatio
White (odds) 60% (1.5) 90% (9) 6
Black (odds) 33% (0.49) 68% (2.1) 4.3
GHBush favorability pre- and post-Gulf War
Pre-disaster Post-disaster OddsRatio
White (odds) 64% (1.8) 90% (9) 5.1
Black (odds) 33% (0.49) 70% (2.3) 4.7
Unless I'm missing something, a logistic regression analysis with disaster and
race coded as dummy variables with an interaction term (disaster x race) would
have a sign for the interaction coefficient indicating that the odds of white
favorability for Bush after a disaster increased more than the increase in
black favorability for Bush after a disaster. This is NOT what I'd expected
after looking at the raw percentages, which to me indicated a
disproproportionate increase in black favorability for the Bushes after
disasters.
Gene Gallagher
UMASS/Boston
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------------------------------
Date: Tue, 15 Jan 2002 02:11:18 GMT
From: Jon Miller <[EMAIL PROTECTED]>
Subject: Re: Modelling Problem
Alexander Hener wrote:
> I have a modelling problem where any help would be appreciated. Assume
> that I want to model a fraction, where the nominator is a sum of, say,
> four continous random variables. I am thinking of using some
> parameter-additive distribution there, e.g. the gamma, since the sum in
> the nominator needs not be negative. The denominator should be continous
> and positive. Now my questions are :
>
> 1. Is anyone aware of distributions which lend themselves to such a model
> ?
Gamma, beta, Weibull, exponential, . . .
Most mathematical probability and stats books have a table of distributions
and some of their properties in an appendix in the back.
> 2. To make things just a little bit more complicated, the (in this case
> four) nominator random variables should be dependent on each other only
> by the nominator.
I don't understand this. Do you mean the variables in the numerator should
be independent of those in the denominator?
> Does anyone know about results for the divisioning of dependent variables
> which I could use in this case?
I guess it depends what you are doing. For example, if you are doing an
analysis of interest rates and you decide that 50% of the rate is based on
the inflation rate and 50% is independent, then you can model the
independent part as one random variable and then add it to the (multiple of)
the inflation rate (that I'm assuming you are modelling as another random
variable) to get the interest rate. Is this what you are asking?
Jon Miller
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------------------------------
Date: Mon, 14 Jan 2002 23:45:27 -0500 (EST)
From: "[EMAIL PROTECTED]" <[EMAIL PROTECTED]>
Subject: Conference calls are safe
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------------------------------
Date: 15 Jan 2002 02:00:48 GMT
From: "EugeneGall" <[EMAIL PROTECTED]>
Subject: Re: Proportionate vs. disproportionate
Rich Ulrich wrote:
>I am not positive, but
>I think I would have objected to "equal % change"
>as =proportionate= by the time I finished algebra in high school.
>
>I know I have objected to similar confusion, on principled
>grounds, since I learned about Odds Ratios.
>
>I suspect that the original sample was small enough that
>the apparent difference in ORs was not impressive.
>--
>
I too think that the odds ratio is the appropriate way to present the data, but
after looking at these results, I can appreciate why the Gallup organization
didn't do so.
The data on racial favorability ratings which Gallup called 'proportionate' not
'disproportionate':
GWBush favorability pre- and post-9/11
Pre-disaster Post-disaster OddsRatio
White (odds) 60% (1.5) 90% (9) 6
Black (odds) 33% (0.49) 68% (2.1) 4.3
GHBush favorability pre- and post-Gulf War
Pre-disaster Post-disaster OddsRatio
White (odds) 64% (1.8) 90% (9) 5.1
Black (odds) 33% (0.49) 70% (2.3) 4.7
Unless I'm missing something, a logistic regression analysis with disaster and
race coded as dummy variables with an interaction term (disaster x race) would
have a sign for the interaction coefficient indicating that the odds of white
favorability for Bush after a disaster increased more than the increase in
black favorability for Bush after a disaster. This is NOT what I'd expected
after looking at the raw percentages, which to me indicated a
disproproportionate increase in black favorability for the Bushes after
disasters.
Gene Gallagher
UMASS/Boston
=================================================================
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problem of INAPPROPRIATE MESSAGES, and archives are available at
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------------------------------
Date: Tue, 15 Jan 2002 02:11:18 GMT
From: "Jon Miller" <[EMAIL PROTECTED]>
Subject: Re: Modelling Problem
Alexander Hener wrote:
> I have a modelling problem where any help would be appreciated. Assume
> that I want to model a fraction, where the nominator is a sum of, say,
> four continous random variables. I am thinking of using some
> parameter-additive distribution there, e.g. the gamma, since the sum in
> the nominator needs not be negative. The denominator should be continous
> and positive. Now my questions are :
>
> 1. Is anyone aware of distributions which lend themselves to such a model
> ?
Gamma, beta, Weibull, exponential, . . .
Most mathematical probability and stats books have a table of distributions
and some of their properties in an appendix in the back.
> 2. To make things just a little bit more complicated, the (in this case
> four) nominator random variables should be dependent on each other only
> by the nominator.
I don't understand this. Do you mean the variables in the numerator should
be independent of those in the denominator?
> Does anyone know about results for the divisioning of dependent variables
> which I could use in this case?
I guess it depends what you are doing. For example, if you are doing an
analysis of interest rates and you decide that 50% of the rate is based on
the inflation rate and 50% is independent, then you can model the
independent part as one random variable and then add it to the (multiple of)
the inflation rate (that I'm assuming you are modelling as another random
variable) to get the interest rate. Is this what you are asking?
Jon Miller
=================================================================
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problem of INAPPROPRIATE MESSAGES, and archives are available at
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------------------------------
Date: Tue, 15 Jan 2002 12:57:31 +1100
From: Glen Barnett <[EMAIL PROTECTED]>
Subject: Re: Modelling Problem
Alexander Hener wrote:
> I have a modelling problem where any help would be appreciated.
> Assume that I want to model a fraction, where the nominator is a sum of,
Do you mean numerator?
> say, four continous random variables. I am thinking of using some
> parameter-additive distribution there, e.g. the gamma, since the sum in
> the nominator needs not be negative. The denominator should be continous
> and positive. Now my questions are :
>
> 1. Is anyone aware of distributions which lend themselves to such a
> model ?
If the fractions are between zero and one, you may wish to consider the
beta distribution for the fraction - if X and Y are independent gamma
r.vs, then X/(X+Y) is beta. If X = X1 + X2 + X3 + X4 is your numerator,
that would seem to suggest something like a beta at first glance.
Glen
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------------------------------
Date: Tue, 15 Jan 2002 12:57:31 +1100
From: "Glen Barnett" <[EMAIL PROTECTED]>
Subject: Re: Modelling Problem
Alexander Hener wrote:
> I have a modelling problem where any help would be appreciated.
> Assume that I want to model a fraction, where the nominator is a sum of,
Do you mean numerator?
> say, four continous random variables. I am thinking of using some
> parameter-additive distribution there, e.g. the gamma, since the sum in
> the nominator needs not be negative. The denominator should be continous
> and positive. Now my questions are :
>
> 1. Is anyone aware of distributions which lend themselves to such a
> model ?
If the fractions are between zero and one, you may wish to consider the
beta distribution for the fraction - if X and Y are independent gamma
r.vs, then X/(X+Y) is beta. If X = X1 + X2 + X3 + X4 is your numerator,
that would seem to suggest something like a beta at first glance.
Glen
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------------------------------
Date: 14 Jan 2002 21:52:32 -0800
From: [EMAIL PROTECTED] (Haipeng Guo)
Subject: CFP: AAAI/KDD/UAI2002 Joint Workshop on Real Time Decision Support and
Diagnosis Systems
[ Sorry if you receive any duplicate copies.]
Call for Participation
AAAI/KDD/UAI2002 Joint Workshop on
Real Time Decision Support and Diagnosis Systems
Monday, 29 July, 2002, Edmonton, Alberta, Canada
http://www.kddresearch.org/KDD/Workshops/RTDSDS-2002/
While AI methodologies are being applied towards increasingly
realistic domains that require timely responses, real-time systems are
coming to incorporate decision-making tools that require more
intelligent capabilities. Many real-world intelligent systems call for
autonomous intelligent agents acting in the face of uncertain
knowledge and limited computational resources. Real-time decision
support and diagnosis systems are two such important application
domains.
- ---Topics
Active research topics that are relevant to real-time decision
support and diagnosis include:
- - real-time expert systems
- - embedded intelligent diagnosis agents
- - anytime uncertain reasoning algorithms and flexible computation
- - cost estimation for resource-bounded computation
- - decision-theoretic planning and deliberative real-time artificial
intelligence
- - real-time Bayesian network inference and learning techniques
- - real-time algorithms for scheduling and situated planning
- - real-time sensor fusion and situation assessment
- - real-time knowledge discovery in databases (KDD)
- ---Format
The one day workshop will include one or more invited talks on
state-of-the-art research problems and methodologies, presentations by
selected participants, and a panel and open discussion sessions on key
topics.
- ---Invited talks and discussion sessions
* Bruce D'Ambrosio (Oregon State University will give a talk on the
state-of-the-art of Real-Time Probabilistic Decision Support and
Diagnosis technologies (45~60 minutes)
* Fabio Gagliardi Cozman (University of Sao Paulo, Brazil) will lead a
discussion session on embedded AI (60 minutes)
* Eugene Santos Jr. (University of Connecticut) will lead a discussion
session on Distributed and Cooperative Problem Solving.
* Marek J. Druzdzel () will lead a session on topics related to
Diagnosis, Real-time Inference, and Sensor fusion.
- ---Attendance
The workshop will be of interest to researchers and practitioners in
the area of uncertain reasoning (UAI), real-time artificial
intelligence (RTAI), and real-time knowledge discovery in databases
(KDD). Participation will be based on submitted research summaries.
We anticipate participation by 25-50 people at the workshop.
- ---Paper Submissions
We encourage submissions containing original theoretical and applied
concepts in real-time decision support and diagnosis systems.
Experimental results are also encouraged, especially on fielded
applications, even if they are only preliminary. We therefore invite
two categories of paper submissions:
- - research papers
* should not exceed 12 pages, including title page
* due Fri 15 March 2002
- - short summaries (including position papers)
* should not exceed 2 pages
* due Fri 29 March 2002
We request that authors prepare papers in the standard AAAI format.
Papers should be submitted in PostScript, PDF, or Microsoft Word
97/2000 file format. Electronic submissions are preferred, but both
types of papers may be submitted by one of the following three
options:
* E-mail a URL pointer to the paper to [EMAIL PROTECTED]
* Attach a PostScript, PDF, or Word file (or .zip, .gz, or .bz2
archive) to [EMAIL PROTECTED]
* Mail 5 hard copies printed on 8.5" x 11" or A4 paper with at least 1
inch margins on all sides.
All submissions should be sent to [EMAIL PROTECTED]
- ---Organizing Chairs
Haipeng Guo (primary contact)
Department of Computing and Information Sciences
p: Kansas State University, 234 Nichols Hall, Manhattan, KS 66506-
2302 * t: (785)539-0278, f: (785) 539-7180 * e: [EMAIL PROTECTED] * w:
www.cis.ksu.edu/~hpguo
Eric Horvitz
Adaptive Systems & Interaction Group, Microsoft Research
p: Microsoft Research, Redmond WA 98052-6399 * t:(425)936-2127 * f:
(425)936-7329, * e: [EMAIL PROTECTED] *
w:research.microsoft.com/users/horvitz/
William H. Hsu (primary contact)
Department of Computing and Information Sciences
p: Kansas State University, 234 Nichols Hall, Manhattan, KS 66506-2302
* t: (785) 539-7180 * f: (785) 539-7180 * e: [EMAIL PROTECTED] * w:
www.cis.ksu.edu/~bhsu
Eugene Santos Jr.
Department of Computer Science and Engineering
p: UTEB, 191 Auditorium Rid., U-155, Storrs, CT 06269-3155, * t: (860)
486-1458 * f: (860) 486-4817 * e: [EMAIL PROTECTED] , * w:
www.cse.uconn.edu/cse/santos.htm
- ---Program Committee (to date)
Daniel Andresen (Kansas State University)
Bruce D'Ambrosio, Oregon State University
Fabio Gagliardi Cozman, University of Sao Paulo
Marek J. Druzdzel, University of Pittsburgh
Haipeng Guo, Kansas State University (Organizing Committee)
Eric Horvitz, Microsoft Research (Organizing Committee)
William H. Hsu, Kansas State University (Organizing Committee)
Henry Kautz, Washington University
Sven Koenig, Georgia Institute of Technology
Mitchell L. Neilsen, Kansas State University
David Poole, University of British Columbia
Eugene Santos Jr., University of Connecticut (Organizing Committee)
Solomon Shimony, Ben Gurion University
Shlomo Zilberstein, University of Massachusetts
- ---Additional information
Please consult the following web page:
http://www.kddresearch.org/KDD/Workshops/RTDSDS-2002/
for more information.
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------------------------------
Date: 14 Jan 2002 21:52:32 -0800
From: "Haipeng Guo" <[EMAIL PROTECTED]>
Subject: CFP: AAAI/KDD/UAI2002 Joint Workshop on Real Time Decision Support and
Diagnosis Systems
[ Sorry if you receive any duplicate copies.]
Call for Participation
AAAI/KDD/UAI2002 Joint Workshop on
Real Time Decision Support and Diagnosis Systems
Monday, 29 July, 2002, Edmonton, Alberta, Canada
http://www.kddresearch.org/KDD/Workshops/RTDSDS-2002/
While AI methodologies are being applied towards increasingly
realistic domains that require timely responses, real-time systems are
coming to incorporate decision-making tools that require more
intelligent capabilities. Many real-world intelligent systems call for
autonomous intelligent agents acting in the face of uncertain
knowledge and limited computational resources. Real-time decision
support and diagnosis systems are two such important application
domains.
- ---Topics
Active research topics that are relevant to real-time decision
support and diagnosis include:
- - real-time expert systems
- - embedded intelligent diagnosis agents
- - anytime uncertain reasoning algorithms and flexible computation
- - cost estimation for resource-bounded computation
- - decision-theoretic planning and deliberative real-time artificial
intelligence
- - real-time Bayesian network inference and learning techniques
- - real-time algorithms for scheduling and situated planning
- - real-time sensor fusion and situation assessment
- - real-time knowledge discovery in databases (KDD)
- ---Format
The one day workshop will include one or more invited talks on
state-of-the-art research problems and methodologies, presentations by
selected participants, and a panel and open discussion sessions on key
topics.
- ---Invited talks and discussion sessions
* Bruce D'Ambrosio (Oregon State University will give a talk on the
state-of-the-art of Real-Time Probabilistic Decision Support and
Diagnosis technologies (45~60 minutes)
* Fabio Gagliardi Cozman (University of Sao Paulo, Brazil) will lead a
discussion session on embedded AI (60 minutes)
* Eugene Santos Jr. (University of Connecticut) will lead a discussion
session on Distributed and Cooperative Problem Solving.
* Marek J. Druzdzel () will lead a session on topics related to
Diagnosis, Real-time Inference, and Sensor fusion.
- ---Attendance
The workshop will be of interest to researchers and practitioners in
the area of uncertain reasoning (UAI), real-time artificial
intelligence (RTAI), and real-time knowledge discovery in databases
(KDD). Participation will be based on submitted research summaries.
We anticipate participation by 25-50 people at the workshop.
- ---Paper Submissions
We encourage submissions containing original theoretical and applied
concepts in real-time decision support and diagnosis systems.
Experimental results are also encouraged, especially on fielded
applications, even if they are only preliminary. We therefore invite
two categories of paper submissions:
- - research papers
* should not exceed 12 pages, including title page
* due Fri 15 March 2002
- - short summaries (including position papers)
* should not exceed 2 pages
* due Fri 29 March 2002
We request that authors prepare papers in the standard AAAI format.
Papers should be submitted in PostScript, PDF, or Microsoft Word
97/2000 file format. Electronic submissions are preferred, but both
types of papers may be submitted by one of the following three
options:
* E-mail a URL pointer to the paper to [EMAIL PROTECTED]
* Attach a PostScript, PDF, or Word file (or .zip, .gz, or .bz2
archive) to [EMAIL PROTECTED]
* Mail 5 hard copies printed on 8.5" x 11" or A4 paper with at least 1
inch margins on all sides.
All submissions should be sent to [EMAIL PROTECTED]
- ---Organizing Chairs
Haipeng Guo (primary contact)
Department of Computing and Information Sciences
p: Kansas State University, 234 Nichols Hall, Manhattan, KS 66506-
2302 * t: (785)539-0278, f: (785) 539-7180 * e: [EMAIL PROTECTED] * w:
www.cis.ksu.edu/~hpguo
Eric Horvitz
Adaptive Systems & Interaction Group, Microsoft Research
p: Microsoft Research, Redmond WA 98052-6399 * t:(425)936-2127 * f:
(425)936-7329, * e: [EMAIL PROTECTED] *
w:research.microsoft.com/users/horvitz/
William H. Hsu (primary contact)
Department of Computing and Information Sciences
p: Kansas State University, 234 Nichols Hall, Manhattan, KS 66506-2302
* t: (785) 539-7180 * f: (785) 539-7180 * e: [EMAIL PROTECTED] * w:
www.cis.ksu.edu/~bhsu
Eugene Santos Jr.
Department of Computer Science and Engineering
p: UTEB, 191 Auditorium Rid., U-155, Storrs, CT 06269-3155, * t: (860)
486-1458 * f: (860) 486-4817 * e: [EMAIL PROTECTED] , * w:
www.cse.uconn.edu/cse/santos.htm
- ---Program Committee (to date)
Daniel Andresen (Kansas State University)
Bruce D'Ambrosio, Oregon State University
Fabio Gagliardi Cozman, University of Sao Paulo
Marek J. Druzdzel, University of Pittsburgh
Haipeng Guo, Kansas State University (Organizing Committee)
Eric Horvitz, Microsoft Research (Organizing Committee)
William H. Hsu, Kansas State University (Organizing Committee)
Henry Kautz, Washington University
Sven Koenig, Georgia Institute of Technology
Mitchell L. Neilsen, Kansas State University
David Poole, University of British Columbia
Eugene Santos Jr., University of Connecticut (Organizing Committee)
Solomon Shimony, Ben Gurion University
Shlomo Zilberstein, University of Massachusetts
- ---Additional information
Please consult the following web page:
http://www.kddresearch.org/KDD/Workshops/RTDSDS-2002/
for more information.
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------------------------------
Date: Tue, 15 Jan 2002 06:48:08 GMT
From: "Mike" <[EMAIL PROTECTED]>
Subject: Re: Buy Book on "Probability and statistical inference"
"Chia C Chong" <[EMAIL PROTECTED]> wrote in message
a1urs0$a8n$[EMAIL PROTECTED]">news:a1urs0$a8n$[EMAIL PROTECTED]...
>
> "Vadim and Oxana Marmer" <[EMAIL PROTECTED]> wrote in message
> [EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> > > On Sat, 12 Jan 2002 14:37:10 -0000, "Chia C Chong"
> > > <[EMAIL PROTECTED]> wrote:
> > >
> > > > Hi!
> > > >
> > > > I wish to get a book in Probability and statistical inference . I
wish
> to
> > > > get some advices first..Any good suggestion??
> > >
> >
> > it depends on your background and your interests. If you can give more
> > details about this then you can get more helpful suggestions.
> >
>
> I am currently doing a PhD in Wireless Communications. My research are is
to
> develop a statistical wireless channel model for the 4th generation
systems.
> I would prefer a books that deal with a lot of pratical examples
especially
> how to fit measurement data to theoretical distributions and perform
> goodness of fit test of their fits.
Chia,
There's been lots of stuff written about wireless communication channel
models - see recent issues of IEEE Transactions on Communications and other
similar journals. One place to start might be to look for books in the
references of articles that describe wireless communication channels.
- -- Mike --
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------------------------------
Date: Tue, 15 Jan 2002 06:48:08 GMT
From: "Mike" <[EMAIL PROTECTED]>
Subject: Re: Buy Book on "Probability and statistical inference"
"Chia C Chong" <[EMAIL PROTECTED]> wrote in message
a1urs0$a8n$[EMAIL PROTECTED]">news:a1urs0$a8n$[EMAIL PROTECTED]...
>
> "Vadim and Oxana Marmer" <[EMAIL PROTECTED]> wrote in message
> [EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> > > On Sat, 12 Jan 2002 14:37:10 -0000, "Chia C Chong"
> > > <[EMAIL PROTECTED]> wrote:
> > >
> > > > Hi!
> > > >
> > > > I wish to get a book in Probability and statistical inference . I
wish
> to
> > > > get some advices first..Any good suggestion??
> > >
> >
> > it depends on your background and your interests. If you can give more
> > details about this then you can get more helpful suggestions.
> >
>
> I am currently doing a PhD in Wireless Communications. My research are is
to
> develop a statistical wireless channel model for the 4th generation
systems.
> I would prefer a books that deal with a lot of pratical examples
especially
> how to fit measurement data to theoretical distributions and perform
> goodness of fit test of their fits.
Chia,
There's been lots of stuff written about wireless communication channel
models - see recent issues of IEEE Transactions on Communications and other
similar journals. One place to start might be to look for books in the
references of articles that describe wireless communication channels.
- -- Mike --
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------------------------------
Date: Tue, 15 Jan 2002 08:45:02 -0500
From: "E. Jacquelin Dietz" <[EMAIL PROTECTED]>
Subject: Duplicate messages
I apologize for the duplicate messages that are appearing in EdStat. I
really don't understand what's going on -- if anyone has any insight
into this, please let me know! It looks like messages that are
originally posted to the newsgroup sci.stat.edu are forwarded to EdStat,
where they appear with one copy of the footer message. Then they
somehow appear in EdStat a second time with a second footer appended.
But they do NOT appear twice on the newsgroup. Messages that are
originally posted on EdStat appear once each place without any problem.
This doesn't make any sense to me, so I really don't know how to try to
solve it. If anyone has any other observations about what is going on,
or any ideas about how to stop it, I'd really appreciate some help!
Jackie Dietz
Listowner, EdStat
- --
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
E. Jacquelin Dietz (919) 515-1929 (phone)
Department of Statistics, Box 8203 (919) 515-1169 (FAX)
North Carolina State University
Raleigh, NC 27695-8203 USA [EMAIL PROTECTED]
Street address for FedEx:
Room 210E Patterson Hall, 2501 Founders Drive
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
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------------------------------
Date: 15 Jan 2002 14:54:04 GMT
From: [EMAIL PROTECTED] (Radford Neal)
Subject: Re: Proportionate vs. disproportionate
In article <[EMAIL PROTECTED]>,
EugeneGall <[EMAIL PROTECTED]> wrote:
> I too think that the odds ratio is the appropriate way to present
> the data, but after looking at these results, I can appreciate why
> the Gallup organization didn't do so.
>
> The data on racial favorability ratings which Gallup called
> 'proportionate' not 'disproportionate':
>
> GWBush favorability pre- and post-9/11
> Pre-disaster Post-disaster OddsRatio
> White (odds) 60% (1.5) 90% (9) 6
> Black (odds) 33% (0.49) 68% (2.1) 4.3
>
> GHBush favorability pre- and post-Gulf War
> Pre-disaster Post-disaster OddsRatio
> White (odds) 64% (1.8) 90% (9) 5.1
> Black (odds) 33% (0.49) 70% (2.3) 4.7
>
> Unless I'm missing something, a logistic regression analysis with
> disaster and race coded as dummy variables with an interaction term
> (disaster x race) would have a sign for the interaction coefficient
> indicating that the odds of white favorability for Bush after a
> disaster increased more than the increase in black favorability for
> Bush after a disaster. This is NOT what I'd expected after looking
> at the raw percentages, which to me indicated a disproproportionate
> increase in black favorability for the Bushes after disasters.
I think you're all reading too much into this data. A simple
examination of the the 9/11 and Gulf War numbers shows that there
is virtually no difference in all four of the numbers (60% vs. 64%,
68% vs. 70%, others identical). Since people's opinions are presumably
influenced by other issues, not to mention the weather at the time the
poll is conducted, drawing any conclusion to the effect that the two
disasters had different political effects would be ridiculous.
As for the data on just one disaster (say 9/11), it's silly to
summarize it, or to describe the changes as "proportionate" or not.
There are just four numbers. Anyone can look at them and draw their
own conclusions. Nothing is gained by attempting to interpret them in
terms of odds ratios. There is no reason to think that a logistic
regression model is going to provide insight into the extremely
complex interactions of factors (most invisible in this data, of
course) that determine people's political opinions. To mention just
one possibility, there may well be groups of people who would never
say they approve of Bush, or never say they don't approve, because of
ideological committments having nothing to do with 9/11, which they
are very unlikely to abandon. Any logistic regression style model
would then be more appropriately applied only to the people with more
malleable opinions. The regression coefficients obtained from this
model (if one could fit it, which one can't, of course) could well be
quite different from those obtained on the whole data set.
Radford Neal
- ----------------------------------------------------------------------------
Radford M. Neal [EMAIL PROTECTED]
Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED]
University of Toronto http://www.cs.utoronto.ca/~radford
- ----------------------------------------------------------------------------
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------------------------------
Date: 15 Jan 2002 14:54:04 GMT
From: "Radford Neal" <[EMAIL PROTECTED]>
Subject: Re: Proportionate vs. disproportionate
In article <[EMAIL PROTECTED]>,
EugeneGall <[EMAIL PROTECTED]> wrote:
> I too think that the odds ratio is the appropriate way to present
> the data, but after looking at these results, I can appreciate why
> the Gallup organization didn't do so.
>
> The data on racial favorability ratings which Gallup called
> 'proportionate' not 'disproportionate':
>
> GWBush favorability pre- and post-9/11
> Pre-disaster Post-disaster OddsRatio
> White (odds) 60% (1.5) 90% (9) 6
> Black (odds) 33% (0.49) 68% (2.1) 4.3
>
> GHBush favorability pre- and post-Gulf War
> Pre-disaster Post-disaster OddsRatio
> White (odds) 64% (1.8) 90% (9) 5.1
> Black (odds) 33% (0.49) 70% (2.3) 4.7
>
> Unless I'm missing something, a logistic regression analysis with
> disaster and race coded as dummy variables with an interaction term
> (disaster x race) would have a sign for the interaction coefficient
> indicating that the odds of white favorability for Bush after a
> disaster increased more than the increase in black favorability for
> Bush after a disaster. This is NOT what I'd expected after looking
> at the raw percentages, which to me indicated a disproproportionate
> increase in black favorability for the Bushes after disasters.
I think you're all reading too much into this data. A simple
examination of the the 9/11 and Gulf War numbers shows that there
is virtually no difference in all four of the numbers (60% vs. 64%,
68% vs. 70%, others identical). Since people's opinions are presumably
influenced by other issues, not to mention the weather at the time the
poll is conducted, drawing any conclusion to the effect that the two
disasters had different political effects would be ridiculous.
As for the data on just one disaster (say 9/11), it's silly to
summarize it, or to describe the changes as "proportionate" or not.
There are just four numbers. Anyone can look at them and draw their
own conclusions. Nothing is gained by attempting to interpret them in
terms of odds ratios. There is no reason to think that a logistic
regression model is going to provide insight into the extremely
complex interactions of factors (most invisible in this data, of
course) that determine people's political opinions. To mention just
one possibility, there may well be groups of people who would never
say they approve of Bush, or never say they don't approve, because of
ideological committments having nothing to do with 9/11, which they
are very unlikely to abandon. Any logistic regression style model
would then be more appropriately applied only to the people with more
malleable opinions. The regression coefficients obtained from this
model (if one could fit it, which one can't, of course) could well be
quite different from those obtained on the whole data set.
Radford Neal
- ----------------------------------------------------------------------------
Radford M. Neal [EMAIL PROTECTED]
Dept. of Statistics and Dept. of Computer Science [EMAIL PROTECTED]
University of Toronto http://www.cs.utoronto.ca/~radford
- ----------------------------------------------------------------------------
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------------------------------
Date: Tue, 15 Jan 2002 14:04:06 -0500
From: Robert R Johnson <[EMAIL PROTECTED]>
Subject: Help finding article
Would someone please help me find the name and
address (e-mail preferably) of the author of the article
"Fall 1998 Salary Survey Results" that appeared on
p. 78 in Visual Basic Programmer's Journal,
September, 1998.
I thank you in advance for any assistance offered.
Bob Johnson
- -~~~~~~~~~~~~~~~~~~~~~~~~~~~
E-mail: [EMAIL PROTECTED]
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------------------------------
Date: Tue, 15 Jan 2002 13:21:57 -0500
From: Vadim and Oxana Marmer <[EMAIL PROTECTED]>
Subject: Re: Buy Book on "Probability and statistical inference"
Casella and Berger "Statistical Inference" is a very popular graduate
level textbook on the topic. It's not related to your field directly, but
it gives introduction to the concepts used in statistics: likelihood,
sufficiency, completeness, statistical decision theory. Also you may want
to get graduate level probability textbook. I recommend to try Shiryayev
"Probability". Again, these books are not applied and rather general, but
you have to know this stuff if you are serious about statistical analysis.
On Mon, 14 Jan 2002, Chia C Chong wrote:
>
> "Vadim and Oxana Marmer" <[EMAIL PROTECTED]> wrote in message
> [EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> > > On Sat, 12 Jan 2002 14:37:10 -0000, "Chia C Chong"
> > > <[EMAIL PROTECTED]> wrote:
> > >
> > > > Hi!
> > > >
> > > > I wish to get a book in Probability and statistical inference . I wish
> to
> > > > get some advices first..Any good suggestion??
> > >
> >
> > it depends on your background and your interests. If you can give more
> > details about this then you can get more helpful suggestions.
> >
>
> I am currently doing a PhD in Wireless Communications. My research are is to
> develop a statistical wireless channel model for the 4th generation systems.
> I would prefer a books that deal with a lot of pratical examples especially
> how to fit measurement data to theoretical distributions and perform
> goodness of fit test of their fits.
>
> Thanks..
>
> CCC
>
>
>
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------------------------------
Date: 15 Jan 2002 10:23:45 -0800
From: [EMAIL PROTECTED] (Sue Turner)
Subject: Course****R (gnu S-plus) programming I: Essentials and Data
Analysis***Minneapolis
XLSolutions Corporation (www.xlsolutions-corp.com) is pleased to
announce a two-day R course,
"R programming I: Essentials and Data Analysis" in:
Minneapolis **** March 28-29, 2002.
This two-day course teaches participants the basics of S and R syntax.
We will concentrate on learning the data structures and commands necessary
for data analysis. This course is designed for those who want to learn
to write programs to accomplish typical data-processing tasks, including
creating graphics. The course will give participants a strong foundation
for becoming a versatile programmer.
Cost for two-day course (payment due after the class).
Commercial $765
Academic $650 Early bird special and group discount: email us!
(Includes course materials, 90 days Technical Support for R,
snacks and continental breakfast!)
We also offer private affordable 1-day or 2-day courses customized to your
needs.
Registration:
Email Sue Turner: [EMAIL PROTECTED]
Phone: 206-686-1578 x221
Visit us: www.xlsolutions-corp.com/training.htm
Benefits:
This two-day course focuses on how to
· Create and Enhance Different kinds of Plots (Scatter plots, Histograms,
Boxplots,.etc)
· Import/export data into the software environment
· Create and manipulate data (vectors, data frames, lists)
· Use the graphical features of the software to explore data
· Perform basics statistics and fit linear regression
· Write functions to automate data analysis tasks
Course Topics:
· An Overview of the Software System: Installation and Demonstration
· Data Objects and Syntax
· Data Manipulation and Management
· Overview of High-level and Low-level Graphics Functions for Data
Exploration
· Creating and Enhancing Plots
· A Comparison of R and S-PLUS
· Writing Functions and Automating Analyses
· Constructing Models and Testing Hypotheses
· Fitting Linear regression modeling
· Tips and Troubleshooting
Course Format:
This course consists of a series of short lectures with demonstrations and
interactive sessions for the participants. Each student is provided with
bound copies of the notes and a CD-ROM containing all examples,
exercises and software used on the course.
Share Your Thoughts:
Are there any additional topics you would like for this course to address?
Would you like for this course to be offered in another city?
Please let us know by contributing to our recommendation list:
[EMAIL PROTECTED]
==========================================================================
R/S programming I: Essentials and Data Analysis. (Minneapolis)
Pre-registration Form (Please email or print and fax: 206-686-1578)
XLsolutions Corporation: For your Solutions needs, Consulting and
Training. www.xlsolutions-corp.com
Title...... First Name ................. Last Name....................
Organization..........................................................
Mailing Address.......................................................
..............................................................
..............................................................
Zip Code...................... Country.............................
Telephone........................... Fax ...............................
E-mail................................................................
Payment will be made by: (1) check (2) invoice (3) bank transfer
Elvis Miller, PhD
Manager Training.
XLSolutions Corporation
206 686 1578
www.xlsolutions-corp.com
[EMAIL PROTECTED]
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------------------------------
Date: 15 Jan 2002 11:27:40 -0800
From: [EMAIL PROTECTED] (Hamid Ghiasi)
Subject: Bayesian Inference for Maximum Entropy
Hello
Is there any algorithm to run maximum entropy using Bayesian Inference.
Hamid
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------------------------------
Date: Tue, 15 Jan 2002 20:24:28 GMT
From: "Marc Schwartz" <[EMAIL PROTECTED]>
Subject: Re: Help finding article
The article is available here:
http://www.devx.com/premier/mgznarch/vbpj/1998/09sep98/ss0998.pdf
The article was done by "VBPJ Staff". E-Mail is: [EMAIL PROTECTED]
Back issues of VBPJ are available here:
http://www.devx.com/premier/archives/default.asp?pubid=1
VBPJ has been replaced by Visual Studio Magazine, which now covers a
wider variety of the Visual languages.
- --
Marc Schwartz
To Reply Remove "-REMOVE.TO.REPLY-" in E-Mail Address
"Robert R Johnson" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> Would someone please help me find the name and
> address (e-mail preferably) of the author of the article
> "Fall 1998 Salary Survey Results" that appeared on
> p. 78 in Visual Basic Programmer's Journal,
> September, 1998.
>
> I thank you in advance for any assistance offered.
>
> Bob Johnson
> -~~~~~~~~~~~~~~~~~~~~~~~~~~~
> E-mail: [EMAIL PROTECTED]
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------------------------------
Date: Tue, 15 Jan 2002 15:35:55 -0500
From: Rich Ulrich <[EMAIL PROTECTED]>
Subject: Re: Empirical data Fitting
[ rearranging to the usual order, with Reply at the bottom ]
> Chia C Chong wrote:
> >
> > Hi!!
> >
> > I have a set of data with some kind of distribution. When I plotted the
> > histogram density of this set of data, it looks sth like the
> > Weibull/Exp/Gamma distribution. I find the parameters that best fit the data
> > and then, plot the respective distribution using the estimated parameters on
> > the empirical distribution. My question is, what kind of statistical test
> > that I should ...
[ ... ]
On 14 Jan 2002 08:15:35 -0800, [EMAIL PROTECTED] (kjetil
halvorsen) wrote:
> A quantile-Quantile plot for graphical comparison is best, if you need a
> numerical test you can use the pearson correlation coefficient between
> the observed and expected quantiles. A table for that test you can ake
> for yourself with simulation.
No, I think that advice is not good, in this instance. Someone
else has mentioned that these three belong to the same family
so that it is possible and most desirable to solve for the value
of the parameter that distinguishes them.
The correlation between those 'quantiles' -- That (I think)
gets you a test like the Shapiro-Wilks which is a fine test for
normality when you compare correlations across a range of
deviant samples. I don't remember its analog being used
for testing between theoretical CDFs; and I suspect it is inferior
to other approaches for (say) strongly skewed distributions.
- --
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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Date: 15 Jan 2002 14:39:23 -0800
From: [EMAIL PROTECTED] (Elias)
Subject: random versus fixed factor
hi
i am a little confused about this topic
(i am a student in psychology), i can not understand the below
(please be patient i am new to this)
if someone can tell me
a) what is a fixed factor, whether we can treat a variable as fixed ?
b) the same about random
c) how formulas are changing? mean square between... (Ms) for mixed or
not designs?
d) Who is Keppel (i read him in many statistic papers but i can
understood) and his contribution in statistic?
e) What is all about Clark and his experiment about verbs and noun?
f) what is the relation of quasi F with fixed and random factor?
g) nested designs what are?
h) What are the implications if a experiment have only 2 random
factors, 2 fixed or 1 fixed and 1 random (and the changes in statistic
types, MS...)
i) when a experiment in anova has 3 factors, it could be all random?
j) what happen about interaction eff? i read that if we have a random
factor we can have interaction without main effects. is right that?
k) And generally i read everywhere random versus fixed factor issue
but nowhere refer what is that (disadv, adv.. implications...),
neither i found something understadable in internet or in our
bibliothic.
l) so i ask sorry for all of these Q and for this person who will have
the persistence to answere all these questions simply and
understadible (i do not know if this place is suitable for these Q so
i ask sorry for 2nd time)
- - i have bought the Howell D.C. book but do not tell much.
- - Also, i have access to some articles but all are very vague and no
clear.
- -A GREAT THANK to anyone who will solve my querries
- -i must ask sorry for my englishs (i am Greek)
Name: Elias
email address: [EMAIL PROTECTED]
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------------------------------
Date: Tue, 15 Jan 2002 23:06:25 GMT
From: janne <[EMAIL PROTECTED]>
Subject: a problem
Lets say I do a x2(chi) test and have the hypothesis:
Ho: there are no differences in opinion between techers and students
Ha: there are differences in opinion between techers and students
Can it only then be:
If X2 obs(observation) is > 2.32(for example) then Ho is rejected. So
if X2 obs is 3.20 Ho is rejected.
Or can it in some cases be:
If X2 obs is < 2.32 then Ho is rejected. So if X2 obs is 1.20 Ho is
rejected.
If you can have < in hypothesis, then when is it < and when is it > I
should use? How do I know which one to use?
I also wonder about t-tests the same question. When do I know if I
should use < or >?
Janne
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Date: Tue, 15 Jan 2002 17:54:24 -0800
From: Stu <[EMAIL PROTECTED]>
Subject: Re: a problem
Hi Janne:
janne wrote:
> Lets say I do a x2(chi) test and have the hypothesis:
>
> Ho: there are no differences in opinion between techers and students
> Ha: there are differences in opinion between techers and students
>
> Can it only then be:
>
> If X2 obs(observation) is > 2.32(for example) then Ho is rejected. So
> if X2 obs is 3.20 Ho is rejected.
>
> Or can it in some cases be:
>
> If X2 obs is < 2.32 then Ho is rejected. So if X2 obs is 1.20 Ho is
> rejected.
Chi sq tests only if the number of categorical items differ. You must
look
at the data to determine the direction. In other words, Chi sq is,
inherently, a one-tailed test.
>
> If you can have < in hypothesis, then when is it < and when is it > I
> should use? How do I know which one to use?
>
> I also wonder about t-tests the same question. When do I know if I
> should use < or >?
This is a little more complex. In a word, it depends.
For example, a customer may believe that a soda dispensing machine
rarely
fills the cup. A < test is appropriate, that is, on the average the
machine dispenses too little.
The manufacture may want to test for >, so as not to dispense too much.
A <> (not equal to) test claims only that the amount dispensed is not
correct. For example. a ball-bearing must be neither too large not too
small.
Stu
Garfield High School
Los Angeles, CA
>
>
> Janne
>
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End of edstat-digest V2000 #610
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