[R] normal distribution

[Spencer Graves]

	  I don't hear a distinction between response variable(s) and potential 
explanatory variable(s).  The standard linear regression and parametric 
ANOVA assumes that the response variable is a linear function of 
parameters to be estimated plus normally distributed noise.  I usually 
judge this by making normal probability plots (qqnorm) of my response 
variables.

	  Where are the 0's that concern you?  Are they in the response 
variable(s) or the potential explanatory variable(s)?  If the latter, 
it's not a problem.  If the former, it is.

hope this helps.  spencer graves

acovaleda at hotpop.com wrote:
> Hi Sirs and Madams.
> 
> My question is more statistical than related with the use of R software and I 
> hope it will not seems so silly and elemental. I'm analyzing  a set of data 
> of some soil organism collected in diferent landscapes, soils taxa, and 
> depths. The sample was performed thinking in a factorial structure with four 
> factors: Specie, Landscape, Soil and Depth. Because not all the species 
> appear in each sample there are so many zeros in the matrix data.
> 
> Checking the normal distribution I'm not sure If I must check it in the 
> original sample data (without zeros) or in the big matrix with zeros. In the 
> first case there is a normal distribution (W = 0,85) but in the second  it is 
> not (W = 0,45). In which data must I check distribution?, Can I proceed to 
> perform a Parametric ANOVA?.
> 
> Thanks
> 
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