On Wed, 17 May 2000, mbattagl wrote in part:
> I have data that measures light intensity with a number of different
> techniques. One of the measurements (a direct measurement and "true"
> measurement of light intensity) involves lots of time, labor, and
> expense. The other techniques are more practical in the sense of time
> and labor, but are indirect measurements (based on canopy structure
> (density, location of holes in the canopy, etc). My goal is to
> determine if the indirect measurements are valid estimates of the
> direct measurements. However, I would also like to predict light
> intensity based on the indirect methods.
On reflection, this sounds like a calibration problem: how to calibrate
a proposed measuring instrument. You might find useful information by
using "calibrate" as a keyword in searching. (Also, responses from
others might be rather more to your point.) Calibration can be thought
of as a subset of regression, and more closely focussed than some of the
responses (including my earlier post!) have been.
< snip >
> For the correlation analysis, I can use Pearson or Spearman analysis.
I think others may have spoken to this point; but I can see little
utility to using Spearman's rank correlation. Ranking your variables
discards all the information about relative distances between different
observed values except their order, which would sort of make all your
careful effort in measuring light intensity directly go for naught.
> To use Pearson, the variables should be normally distributed.
Nothing in the definition of a correlation coefficient calls for any
distributional assumptions at all, except that the relationship being
described be, at least approximately, linear. When one gets to the
point of wanting to compare one value of r with another in a
statistical hypothesis test, it is necessary to make some assumption
about the relevant distribution(s), regardless of one's choice of
coefficient, or to simulate the relevant sampling distribution
empirically.
But it is not at all clear, as several others have remarked,
that your problem is usefully addressed by measuring or comparing
correlations.
< snip, the rest >
-- DFB.
------------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 603-535-2597
184 Nashua Road, Bedford, NH 03110 603-471-7128
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