A message from a colleague on Pearsons r and other statistics

[Dr. Don Kraft]

  In recent times there have been articles now in press in JASIST with issues
at stake that need clarification.  Pearson's r does have the characteristic
of being responsive to 0s, and this may affect the outcome of the analysis,
depending upon what the purpose of the analysis is.  My basic point still
holds:  If people think that Pearson's r is distortive because of this
characteristic, then it is beholden upon them to demonstrate in a practical
manner how this can affect conclusions and how a measure that does not
distort in this manner can lead to a different interpretation of the data.
This some authors adamantly refused to do.  Mathematical fine
points are all very well and good, but there needs to be a "so what"
section at the end.  I have spent the last few years reading Karl Pearson,
R.A. Fisher, Student, Richard von Mises, Bortkiewicz, etc., and their
mathematical capabilities far exceeded those of Rousseau and company.
However, their papers--sometimes described as "a jungle of
formulae"--always had "so what" sections, in which the issue at stake was
clearly stated in clear language and pictures.  If people want a model,
then they should read the 3rd 1911 edition of Karl Pearson's "The Grammar
of Science," where he explains contingency and correlation in clear terms
to laymen.  It is a model of clear thinking, which is often lacking in
present-day work.
Stephen J Bensman
notsjb at lsu.edu