What about trying a qqplot to see how the distribution fits...
   
  For the normal distribution thta is very stright forward, use qqnorm.
   
  To test gamma distribtution (or any other) do some thing like this 
   
  n<-length(data)
  for(i in 1:n){
  prob<-(i-1/3)/(n1/3)
  }
  quantiles<-qgamma(prob,shape=mean(data)/var(data),scale=var(data)/mean(data)}
   
  qqplot(data,quantiles)
   
  If the distribution is a good for, you should a stright line, like wiht a qqnorm plot!
   
  Good luck!!
   
  Elizbaeth Lawson

David Zhao <wzhao6898@gmail.com> wrote:
  Hi there,

I'm a newbie, plesae bear with me.
I have a dataset with about 10000 ~ 30000 data points. Would like fit to
both Gamma and Normal distribution to see which one fits better. How do I do
this in R? Or I could do a normality test of the data, if it's normal, I
then will do a normal fit, otherwise, a gamma fit. But again, I don't know
how to do this either.
Please help!

David

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