In talk.politics.drugs Szasz <[EMAIL PROTECTED]> wrote:
> Erkki Komulainen <[EMAIL PROTECTED]> wrote in message 
>news:<atd490$5ql$[EMAIL PROTECTED]>...
>> In sci.stat.edu Brian Sandle <[EMAIL PROTECTED]> wrote:
>> 
>> : First mistake: The Pearson product-moment correlation is not a rank 
>> : correlation.
>> 
>> Spearman's rank correlation IS Pearsons PMC applied to ranks (instead of
>> original raw/z-scores). The above seems to stress the difference in an
>> odd way. 
>> 
>> Erkki

>   Thanks Erkki! You make me happy I took multivariate statistics. That
> makes Sandle still zero for zero.

>> _________________________________________________________________
>>    <http://www.helsinki.fi.invalid/people/Erkki.Komulainen/>

So I have just taken a quick look at a text used for teaching statistics
in universities. That is Bruning and Kintz. It is very good with examples 
of calculations using many different methods, including multivariate. And 
it has very clear tables of how number of subjects affects the 
significance calculation. 

But if you were hurrying, and just looked at the calculation example for
Pearson product moment correlation, you would not see the *assumptions*
you make when using it. Yes you would see that you use it when you have 
actual scores attained by each subject, rather than just who is better 
than who. And you would see you were working with who is better than who, 
without knowing the scores, in Spearman's rank correlation.

But here is a little question, and I am making it a little ridiculous.

If you know the scores, then you also have the rank order, best to least.
So you could use either test, if you know the scores.

Now what Erkki said could be inferred to mean that which test you use 
depends on scores or not.

You use the Spearman test if you do not have scores, but if you have the 
scores, why bother with the Pearson test, because you can use the Spearman 
anyway, and if you are working by hand, it is about 1/3 the work. Why? 
More to it?


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