An interesting problem have arised during discussion of the
origins of "eigenvalue".
My own point of view is that ANOVA is just a particular case
of regression analysis with dummy (1/0) regressors and
either fixed or random effects. Block orthogonality of
regression matrix in the special case of ANOVA makes it
possible to decompose the sum of squared residuals (and
variance) into several components.
If people misuse the term ANOVA then what is it's correct
meaning? Is it a statistical model which is different from
regression model y=Xb+e? Then there must be some clear
formal discription.
-----------------------------
Alexander Tsyplakov
Novosibirsk State University
http://www.nsu.ru/ef/tsy/
Elliot Cramer wrote...
> Werner Wittmann <[EMAIL PROTECTED]>
wrote:
> : inverting the
> : correlation matrix to get the effects was too
complicated to compute by
> : hand, so Sir Ronald developed the ANOVA shortcut.
>
> hardly. They do have some mathematics in common (through
use of dummy
> variables which some of us think is for dummies). they
are comceptually
> completely different/ Unfortunately many people misuse
ANOVA because they
> think of it as regression analysis.
> : I'm always teasing my colleagues and students, if you
spent one year
> : learning ANOVA and one year multiple regression you've
wasted almost one
> : year of your life.
> you can learn the mathematics of regression analysis in 10
minutes but
> you're still a long way from understanding either it or
ANOVA
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