Which test(s) for analyzing yes-no answers for control vs treated conditions To keep it simple, I have sets of data in which I have a control and a treated sample. The data I obtain is "yes" or "no" (0 or 1) for a particular behaviour. I have 150 data points for each condition (150 for control, 150 treated), obtained across 3 experimental runs, which I intend to pool. They are not paired in any way.
Which test would you recommend? I am currently thinking that binary logistic regression is the best choice, but I'm not sure. I am a biologist and not a mathematician, so please keep that in mind :)
 A: A binary logistic regression would work, for the same reason that you can use a regression when you want to compare two sample means.
However, it may be more apparatus that is required. 
With a small sample, one might consider a binomial test. In this case, your sample sizes are nice and big, so a straight out proportions test should be effectively indistinguishable from it and a little simpler to deal with.
However, since you have three experimental runs it might be worth including experimental run as a covariate (even though if all is well it should not have a covariate effect). In that case, you could use logistic regression to do teh comparison incorporating the experimental run variable, or you could look at a chi-square test to achieve basically the same thing (though if you want a one-tailed test, the first thing would be better).
A: Since your metric is a proportion, the hypothesis test for proportions is the best choice.
This pdf can help you
A: A proportion test as zeferino suggest, or also a $\chi^2$ test or the Fisher exact probability test. 
