His name is Chris Jordan, from "a manufacturing
company." Why he chooses to keep it secret is
anybody's guess, but of course it is rude.
His problem is that he has calculated a response
using a mathematical formula that apparently is
well represented by a quadratic, and hence R^2 is
near unity -- the difference is likely due to
rounding. It is not a statistical problem. The
design, by the way, is not D-optimal, but rather
has an efficiency of about 20%.
Rich Ulrich wrote:
>
> (I am just addressing a single point.)
> On 30 Sep 2000 14:06:59 -0700, [EMAIL PROTECTED] (Donald Burrill)
> wrote:
>
> < concerning >
> > On Sat, 30 Sep 2000 [EMAIL PROTECTED] wrote:
> < snip, most >
> > > My adjusted R square is also very close to R Square.
>
> DB>
> > As is natural for R very close to 1.
>
> - but how close is "very close"? I don't think it can be,
> with 30/31 as the R-squared expected by chance.
>
> Using the adjusted R-squared formula in Cohen and Cohen,
> the distance from 1.0 will be 30 times as big as the observed,
> so that .9954 will be shrunk to .86. Assuming that you do start
> with the full number of variables in the equation, as is usually
> recommended. But you still get "a lot" of shrinkage by my
> book, even if you say the error is (say) only 10 times as
> big as the observed error of 0.0046.
>
> --
> Rich Ulrich, [EMAIL PROTECTED]
> http://www.pitt.edu/~wpilib/index.html
--
Bob Wheeler --- (Reply to: [EMAIL PROTECTED])
ECHIP, Inc.
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