Re: Explaining a Log transformaton on a dependent variable

In article <1177354125.279262.69720@xxxxxxxxxxxxxxxxxxxxxxxxxxx>,
<G_FAROG@xxxxxxxxxxx> wrote:
Hello,

I new to multiple regression and unfortunitly had to do a log
transformation on the dependent variable to fix normality issues. My
problem now is trying to explain the meaining of the final model/
formula with the log function. My final model has three independent
varaibles as predictors (they were centered) and conceptually I am
stuck and not able to explain my model with the log transformation.
Could anyone kind of walk through a explanation? Model for discusion
purposes: Y=10 + .005W + .07H + 1.2P.

Thank you for your assistance,
Greg

Do not transform to "fix normality issues"; normality
is the least important condition for a regression to
be an appropriate thing to do.

--
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, Department of Statistics, Purdue University
hrubin@xxxxxxxxxxxxxxx Phone: (765)494-6054 FAX: (765)494-0558
.

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