On 14 Dec 2002 05:30:59 -0600, Brian Sandle <[EMAIL PROTECTED]> wrote:
[snip, various stuff] > > 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. To this statistician, the use here of the word 'assumptions' seems unique. Yes, when we have certain data -- ranks -- we get the Spearman when we compute the Pearson. We can compute a Pearson correlation regardless of assumptions about outliers, etc., and what we sacrifice might be (a) the test where we can rely on p-levels, and (b) a test on 'something else' - such as, ranks. Computers make this all so much simpler. That is, I think I now prefer to drop all the special names when the r's being the usual Pearson. Instead, I talk about doing a 'rank-transformation' to the data; and whether that is desirable or useful or damaging. [ snip] > 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? Beg-pardon -- Who works by hand? I will second the suggestion that you drop the subject, or at least, take sci.stat.edu off the line for newsgroups, if there is not a statistical question. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
