Thanks for the help. 
I would like to explain my problem.
I have sample of scores from tests which varies form 0 to 35.
Now, i want to find out the best fit distribution for this data. I need to
order the distributions based on their best fit.
For this i am using the function fitdistr(). [One of the Ref.used : FITTING
DISTRIBUTIONS WITH R by Vito Ricci. ]

 Example:
> scores<-sample(0:35,500,replace=T)
> normalfit<-fitdistr(scores,"normal")
> normalfit
    mean          sd    
16.8460000   10.1361869
( 0.4533041) ( 0.3205344)
> normalfit$loglik
[1] -1867.525
 > kstestnormal<-ks.test(scores,"pnorm",16.8460000, 10.1361869) # for the
measure of goodness


1) Am i doing the right thing?
2) If yes, can't i follow the same procedure for all the distributions
supported by fitdistr? With the start values wherever necessary?
3) Do I have to consider/worry about the warnings that I get? 

Thanks

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