I don't have a good reason. I was concerned about the binomial data so I was searching with that being the key word, but I must have overcomplicated the issue. I just looked up the assumptions of the two-sample proportions test and they seem reasonable (see below, am I missing assumptions?). I know that any time I pick a certain test, I need to check that the assumptions are met, but with these assumptions I don't really need to check anything, right? Either the data meets these criteria or it doesn't. Also, is the correct R command prop.test? Why would one use Welch's t- test? Is it because the two sample proportions test is perfect for binomial data, so we really don't to go to Welch's (Which would be better suited for continuous data?)

Thank you again.

The sampling method for each population is simple random sampling.

The samples are independent.

Each sample includes at least 10 successes and 10 failures.

Each population is at least 20 times as big as its sample.