I am hoping to understand best way to test statistical significance between 2 dependent population groups.
For example, consider a usability test. When 100 subjects were tested, 50 of them clicked (=50% click rate). However, 50 of the subjects were male, 40 of whom clicked for an 80% click rate for males.
The question is that 80% statistically significant? In other words, do men click more than the population as a whole? I think I need to use a paired $t$-test, however unsure as what I would use as the mean, since these are all population proportions.
40/50-(50-40)*(100-50)/(40/50)=-624.2? The male click rate is
40/50=80%, and the female click rate is
(50-40)/(100-50)=20%? If 1 of 1 male clicked, you mean that you will have a larger male click rate (from 80% to 100%), but what becomes insignificant?
male click rate = 0or
male click rate = female click rate, or others? Please edit your question to clarify. $\endgroup$