In article <[EMAIL PROTECTED]>,
Alan McLean <[EMAIL PROTECTED]> wrote:
>'No collinearity' *means* the X variables are uncorrelated!
>The basic OLS method assumes the variables are uncorrelated (as you say). In
>practice there is usually some correlation, but the estimates are reasonably
>robust to this. If there is *substantial* collinearity you are in trouble.
The basic OLS method assumes NOTHING about the correlation
of the X variables, as long as there is no linear combination
which is constant. Polynomial regression almost always has
the X variables correlated.
If, for example, X_1 and X_2 are the "independent" variables,
and X_2 is replaced by X_2 + X_1, the coefficients would be
different, but the regression equation would be the same.
--
This address is for information only. I do not claim that these views
are those of the Statistics Department or of Purdue University.
Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399
[EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558
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