On 05/06/2012 10:54 AM, Yong Shen wrote:
Dear all,
I have two questions about data normality.
I used stepwise multiple regression to determine which variables contributed
to tree growth, and want to built a model to explain tree growth. Sample size
is about 50 tree species, I think it is not a large sample size, and some
variables are not normal distribution.
1. Do I have to transform them to normal distributions before I perform
multiple regression?
No. The only area where a Normal assumption comes in is that the
residuals are normally distributed. So you can happily fit the model
without worrying about normality until after you've got the model.
2. Two variables can not transform to normal distributions although I used some
methods (e.g log, sqrt, boxcoxfit), what should I do for the two variables?
Leave them as they are.
Advice that makes life simpler - always the best sort.
Bob
--
Bob O'Hara
Biodiversity and Climate Research Centre
Senckenberganlage 25
D-60325 Frankfurt am Main,
Germany
Tel: +49 69 798 40226
Mobile: +49 1515 888 5440
WWW: http://www.bik-f.de/root/index.php?page_id=219
Blog: http://blogs.nature.com/boboh
Journal of Negative Results - EEB: www.jnr-eeb.org
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