On Fri, 30 Jun 2000, dennis roberts wrote:
> interesting but ... 3 questions:
>
> 1. how can the r squared for the best model be 100% when, the errors
> are not all 0s?
R-sq is not 100% exactly, it is reported as 100.0%.
Examining the SS reported shows that R-sq = 3361.7/3361.9 = 99.994%,
I've enjoyed the comments about polynomial regression. There is a cute joke
that relays the dangers of extrapolating a model.
Two statisticians were travelling in an airplane from LA to New York. About
an hour into the flight, the pilot announced that they had lost an engine,
but don't worry, the
Bob Hayden wrote:
> Tom Moore's original request for data well fit by a cubic tacitly
> implied that it's actually pretty unusual for a cubic (or higher order
> polynomial) to be a good choice. Perhaps Tom even doubted that it
> would EVER be a good choice, and wondered if anyone could provide a
Paul Velleman wrote:
> > I'd rather fit log(wt) on day.
and Donald Burrill responded:
> Agreed. (Any day!-)
> This has the further virtue of permitting "doubling time" to be
> defined and estimated, for the range in which the exponential growth
> function appears to be an adequate description.
On Sat, 1 Jul 2000, Paul Velleman wrote:
> I'm not real comfortable with a polynomial model that takes nearly
> half the available degrees of freedom and offers no theoretical
> motivation.
"Comfortable" is not a word that much occurs to mind in the context of
polynomial models. From the po
Hi
I've been away and must have missed this question. I am always on the
lookout for good regression data. I have my students fold boxes and find
volumes based on the length x of the square cut from the corners to form
the box. I think it's the January,2000 Mathematics Teacher which has an
art
I share Paul's concern about fitting higher order polynomials. My
impression was that Don Burrill was not advocating this and prefered
the exponential model Paul mentioned, presenting the polynomial
approach as one used by some students. I think Don was trying to
indicate the best possible solu
At 4:21 AM -0400 7/1/00, Donald Burrill wrote:
As I vaguely recall, I found this years ago in Snedecor and Cochran.
...
> Using linear through cubic predictors almost works, but has the
>interesting defect of predicting a negative weight for day 6; since one
>clearly doesn't want to stop a
On Fri, 30 Jun 2000, Bob Hayden wrote:
> Tom Moore asked...
>
> Does anyone know of a good example of cubic regression that you'd be
> willing to share?
and Bob replied with an example. Here's another; Bob, would you forward
it to Tom, as I don't have his addre
interesting but ... 3 questions:
1. how can the r squared for the best model be 100% when, the errors are
not all 0s?
2. we are talking about a model that goes from an r squared of 99.5% ... to
(nearly) 100% ... is this important?
3. while there is a dinky gain in r squared ... it comes in rela
Tom Moore asked...
- Forwarded message from Thomas L. Moore -
Hello,
Does anyone know of a good example of cubic regression that you'd be
willing to share?
Thanks.
- End of forwarded message from Thomas L. Moore -
I don't know if this is what Tom had in mind, but
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