Re: statistical similarity of two text

2001-07-18 Thread Donald Burrill

On Tue, 17 Jul 2001, Cantor wrote:

 Does anybody know where I can find program on the website which [can] 
 compare two texts/articles and settle whether or not they are similar 
 assuming any significant level.

Sorry, Cantor:  this is not possible, in general.  
 One can discover whether two (or more) things _differ_ (on some 
quantitative measure) at a specified significance level (when this is a 
reasonable thing to do -- it isn't always reasonable), but the formal 
definition of significant in statistical analysis does not permit 
discovering whether two (or more) things are _similar_.  
 However, it may suffice for your purposes to discover that two things 
are not different enough that you can tell them apart (which is not the 
same thing as discovering that they are the same), on whatever measure 
(or set of measures) you choose to analyze.  Whether this be a useful 
outcome or not depends heavily on how much information you have (that 
is, on the size of the sample available) on the things being compared. 

In any case, the hard part is defining the characteristics, or  
properties, or measures, on which the two texts/articles are to be 
compared. 

 
 Donald F. Burrill [EMAIL PROTECTED]
 184 Nashua Road, Bedford, NH 03110  603-471-7128



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Re: EdStat: Probabilistic inference in resampling?

2001-07-18 Thread Herman Rubin

In article [EMAIL PROTECTED],
Robert J. MacG. Dawson [EMAIL PROTECTED] wrote:

Herman Rubin wrote:

 I consider the Fisherian one to be the only relevant one.
 In fact, I do not think it goes far enough; at best,
 probability is a property of the real world like length
 and mass.  


   On the contrary: length and mass are abstractions that approximately
describe certain aspects of the real world (quantum
mechanics demonstrates this.) They can also both be used, advan-
tageously, to describe other aspects of the real world other than 
those that we normally associate with them (for instance, dimensional
analysis makes good use of the fact that the natural dimension of 
capacitance is length...)

I should have said that probability should be an assumed 
property of the real world like length and mass.

Abstract models are mental; they are not derived from the
real world, but rather selected if they fit.  Einstein
(I do not have the reference) was one of the few to see
that this is the case.

   Probability works like that too. Mathematically probability
is very simple and paradox-free;  it exists only in the sense 
that 24-dimensional quaternionic space or the Monster Group exist.
Various real-world things behave in roughly the same way: both 
long-run frequencies (the frequentist application of probability
theory to the real world) and degrees of belief subject to certain
mental disciplines that individuals may or may not adhere to (the 
Bayesian application).

The frequentist application depends heavily on strong prior
assumptions.  The assumption of independent trials with the
same probability is effectively untestable; at best, it is
approximately true, but we act as if this approximation
holds very far out in the tails.  The frequentist view of
testing is even more questionable.

   (It is undoubtedly true that in the real world a person may well
believe incompatible things. The word believe is not the3 property
of the statistical community and we cannot say oh no you don't to such
a person. However, those whose degrees of belief in related events do
*not* fit the Bayesian yoga  and who are prepared to bet when the odds
give them an edge according to their own beliefs can be reliably (in the
long run) relieved of their stakes. This gives some objective basis to
the idea of consistent belief systems.)

   -Robert Dawson


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-- 
This address is for information only.  I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054   FAX: (765)494-0558


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Re: Regression to the mean,Barry Bonds HRs

2001-07-18 Thread Rich Ulrich

On 17 Jul 2001 15:23:29 -0700, [EMAIL PROTECTED] (dennis roberts) wrote:

 At 04:08 PM 7/17/01 -0400, Rich Ulrich wrote:
 
 But, so far as I have heard,  the league MEANS stay the same.
 The SDs are the same.  There is no preference, that I have ever
 heard, for records to be set by half-season, early or late, team
 or individual.  My guess is that association between talent
 and winning  (or hitting, or pitching, etc.) remains the same.

dmr  
 but, individuals are not half tests ... and, the mean # of homers in the 
 second half is not the same (except by coincidence) to the # of home runs 
 in the second half ... the original post was not about TEAM stats ... which 
 are fixed in the sense that if one team loses alot ... another team wins 
 alot ...

I am not at all convinced of a difference.

Sporting statistics still seem to me to be exactly the same 
as parallel tests in psychology.  Team stats, I agree, might
seem MORE or LESS parallel - more parallel, since the 
means have to be the same.  But UP for one has to be DOWN
for another.

Exactly like homers, the IQ score in May is not exactly the same as
January, except by coincidence.  If you were scanning a group,
you would expect RTTM  in either instance, exactly as described
by the correlation, etc.

dmr 
 every individual player could get better the 2nd half of the season ... or, 
 get worse ... in terms of batting ... 
 [ ... ]
To be sure:  I was referring to performance *in*  a 2nd half, 
and not as statistics that are cumulative.

 - History says, a big change is less likely for baseball than 
for a psych-test.  If you take your parallel IQ test several months
apart, I suppose you could sprain-a-brain in the meantime.
Or drop out of school and miss the test entirely.

You can read in the sports page that a team has caught fire
or is in the slumps.  However, so far as I have seen,  the 
longest streaks are amazingly consistent with chance.  
I have seen estimates, for the major US professional sports.  
The estimates for individual streaks are not beyond chance, either.
(Some of these were in articles published in the ASA journal
named Chance, over the last several years.)

-- 
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html


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Symposium 2001 of Statistics Canada

2001-07-18 Thread Simon Cheung

Statistics Canada is holding its 18th International Symposium on 
Methodological Issues from October 16 to October 19, 2001, in Hull, 
Quebec, just minutes away from Ottawa.
 
The theme of Symposium 2001 is Achieving Data Quality in a Statistical 
Agency: a Methodological Perspective.  This symposium will provide 
an ideal forum for statisticians, researchers, academics, data analysts 
and persons interested in meeting the challenges of a statistical agency 
to discuss, exchange knowledge and share experiences.

Three workshops will be held on October 16th. They are Non-sampling 
Errors by Clyde Tucker of the Bureau of Labor Statistics, USA; An 
Overview of Statistical Quality Control Methods Used in Statistical 
Agencies by Walter Mudryk of Statistics Canada; and Implementing 
Continuous Quality Improvement in a Statistical Agency by David Marker 
and David Morganstein of WESTAT, USA.

Visit www.statcan.ca/english/conferences/symposium2001 where you will 
find the Symposium 2001 Program and the Registration Form. You can also 
contact us by email at [EMAIL PROTECTED] 

Register now!



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