Speaking -- well, writing, if you want to quibble :-) -- as an erstwhile
engineer, Mike, was it not obvious that the response you cite below from
"another NG" is identical to, or equivalent to, advice offered by several
respondents (including Bob Hayden, whom you also quote below, and me) on
edstat?
-- Don.
On Fri, 2 Jun 2000, Mike Stephenson wrote:
> Thanks again for everyone's input. It definitely helped me. I'm an
> engineer, not a statistician and sometimes it shows. :)
>
> I did get a response on another NG, which I think will give me an
> acceptable way to calculate a correlation coefficient that might have a
> little more meaning as how good the fit is. Here it is:
>
> If your true sample values are (x,y) and your model calculates an
> estimated value y_estim = m(x), then the empiric correlation factor R
> between y and y_estim might help you. R^2 is used as a "goodness of fit"
> measure for linear models. It can be interpreted as a ratio of variances:
> R^2 = the variance of y_estim divided by the variance of y. The variance
> of y_estim is the part of the variance of y that is "explained" by the
> model.
>
> Sample plots of y_estim over y may be a good illustration as well.
>
> Bob Hayden <[EMAIL PROTECTED]> wrote:
>
> > I would agree with most of the folks questioning whether this is a
> > good idea, but if you really want to do this...
> >
> > You can compute the correlation of x and 1/y
> >
> > OR
> >
> > You can take the y-values (not 1/y values) predicted by your equation,
> > subtract them from the observed y-values to get residuals, square the
> > residuals and sum the squares, and then find the percentage reduction
> > in the sum of squared residuals from the curve as compared to
> > residuals from the mean. This will be a kind of "r^2" whose square
> > root you can take (after converting to a decimal fraction).
> >
> > What if anything these numbers mean and how they might be interpreted
> > I leave to others!-)
------------------------------------------------------------------------
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
===========================================================================
This list is open to everyone. Occasionally, less thoughtful
people send inappropriate messages. Please DO NOT COMPLAIN TO
THE POSTMASTER about these messages because the postmaster has no
way of controlling them, and excessive complaints will result in
termination of the list.
For information about this list, including information about the
problem of inappropriate messages and information about how to
unsubscribe, please see the web page at
http://jse.stat.ncsu.edu/
===========================================================================
