Hello forum friends!
So I have been using excel to compare if two groups are statistically significantly different. My null Hypothesis is that these two groups are the same (or that there is no difference between groups).
When comparing my Hispanic population vs non-Hispanic population and their knowledge of STIs (based of yes/no data converted to 1/0 data), I used two-tailed t-tests assuming equal variance (excel: t-test 2 tails, type 2).
However, I was told that this was wrong because t-tests compare means and I would want to do a proportion comparison.
Thus, I computed p-values using Fisher's exact test (and/or chi square test).
My question is: which one is the correct method of testing statistical significance?
I got the SAME p-values with both tests (t-tests vs Fisher's) and was wondering why that is so.
Much thanks on advance,
Lilo
So I have been using excel to compare if two groups are statistically significantly different. My null Hypothesis is that these two groups are the same (or that there is no difference between groups).
When comparing my Hispanic population vs non-Hispanic population and their knowledge of STIs (based of yes/no data converted to 1/0 data), I used two-tailed t-tests assuming equal variance (excel: t-test 2 tails, type 2).
However, I was told that this was wrong because t-tests compare means and I would want to do a proportion comparison.
Thus, I computed p-values using Fisher's exact test (and/or chi square test).
My question is: which one is the correct method of testing statistical significance?
I got the SAME p-values with both tests (t-tests vs Fisher's) and was wondering why that is so.
Much thanks on advance,
Lilo