Hi, I have a dataset that has 2 groups of samples. For each sample, then 
response measured is the number of success (no.success) obatined with the number 
of trials (no.trials). So a porportion of success (prpop.success) can be 
computed as no.success/no.trials. Now the objective is to test if there is a 
statistical significant difference in the proportion of success between the 2 
groups of samples (say n1=20, n2=30).

I can think of 2 ways to do the test:

1. regular t test based on the variable prop.success
2. Mann-Whitney test based on the variable prop.success
2. do a binomial regression as:
    fit<-glm(cbind(no.success,no.trials-no.success) ~ group, data=data, 
         family=binomial)
    anova(fit, test='Chisq')

My questions is:
1. Is t test appropriate for comparing 2 groups of proportions?
2. how about Mann-Whitney non-parametric test?
3. Among the 3, which technique is more appropriate?
4. any other technique you can suggest?

Thank you,

John


      
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