On Wed, 20 Feb 2002 19:30:19 -0000, "Chia C Chong" <[EMAIL PROTECTED]> wrote:
> > "Vadim and Oxana Marmer" <[EMAIL PROTECTED]> wrote in message > [EMAIL PROTECTED]">news:[EMAIL PROTECTED]... > > You can start with checking if they are correlated. It's simpler to do. If > > you find that they are correlated then you have the answer to your > > question. > > If you find that they are uncorrelated and you have a reason to believe > > that they may be not independent anyway then you can look for more > > advanced tests. > > Can you give some examples of more advanced tests that can be used to test > the depedency of data when there these data are uncorrelated?? You can check for an obvious non-linear (say quadratic) fit. WHAT is your 'reason to believe that they may be not independent'? Anything that makes any pattern, at all, is 'dependent.' So there is an infinite variety of tests conceivable. So the *useful* test is the one that avoids 'Bonferroni correction," because it is the one you perform because you have some reason for it. -- 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/ =================================================================
