Rafal wrote:
> I have a network of sample plots distirubuted in a regular grid in
> researched area. On each plot I measured my dependent variable and set of
> 'independent' (as independent as real world relations can be where
> everything sems to be related to everything). Now I am using multivariate
> regression to create a model  allowing to estimate dependent variable from
> set of independent. Dependent variable has normal distribution. The most
> correlated with dependent variable seems to be height above sea level
> although its distribution is very different from normal because of shape of
> area where research was made. My questions  are:
> 1)Should I try to transform it to obtain distribution more similar to normal
> as literature suggests?
> 2) When forward or backward stepwise regression is used, is there a limit
> for the number of independent variables one can take into procedure? Does
> the literature which suggest taking 5 to 20 times less variables then cases
> speaks about final equation obtained from frinished regression procedure or
> amount before stepwise procedure?

The distribution of the predictor/independent variables isn't assumed to
be normal in multiple regression. The important thing is the
distribution of the residuals in the multiple regression (which are
assumed to be sample from a normal population). Plot the residuals of
your model - you may not have a problem.

Thom
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