Thanks for all the replies. Another question, if we see: position 1 position 2 C S A D A D W F E A F A A A A ... ... ... A A
Based on defination of Phi correlation coefficient, the correlatio coefficient between C at position 1 and S at position S = 1. Supposed data is many , X^2 is also significant. But I guess it is possible that it is just a chance that C and S happen together. I mean maybe some artificial covariance happened there. Is there any way to elimite the covariance? Thanks a lot Eric Bohlman <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > Rich Ulrich <[EMAIL PROTECTED]> wrote in > news:[EMAIL PROTECTED]: > > > How do *you* describe the correlation of (say) > > height with weight of a set of objects, where > > every object is exactly the same height? > > > > - well, there is no "co"- variation, so you might > > settle for zero. But I think that depends on how > > limited your needs are. > > It's rather odd that "intuitively" to me, it depends on whether or not you > treat one variable as "independent" and another as "dependent." If I look > at a scatterplot where all the points are arrayed along a horizontal line, > my first thought is "zero correlation" whereas if I see one where all the > points fall on a vertical line, my first thought is "not enough information > to tell whether there is a correlation." But mathematically, that's > nonsensical; zero correlation implies a roughly circular pattern of points > (I like Stephen Jay Gould's heuristic that correlation measures the > "skinniness" of a scatterplot), and it's rather obvious that if you simply > interchange axes, there's no difference between the two situations. > > I think this is a case where we're encountering what Sir Francis Bacon > called an "idol," a prejudice of thought that distorts our view of reality. > We want to believe that correlation is defined for any pair of random > variables, but in fact it's meaningless if one of those RVs has all its > density concentrated at a single point. We somehow expect that because we > call it a random "variable" it has to *vary*, but the definition of a > random variable is merely "a function whose domain is a probability space" > and constants meet that definition. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
