
Hypothesis Test
I ve had and am having the hardest time trying to figure out which hypothesis test to use for the following:
A 2 tailed test
Known: n = # of trials
mean for sample 1
mean for sample 2
n's are <30 AND population variances are NOT known. Since variances are not known, I should use a ttest, but then in order to get Sp^2 I need the variances. Am I trying to use the right test?

Do sample 1 and sample 2 follow any law? n: # of trials seems like it could be a binomial law? In this case you can find the std deviation with the definition of the variation in a binomiale law (mean = E(x) = np; then find var = np(1p) => std dev = sqrt(var))
If you give the whole question it might be easy to figure out

well, here's the original problem:
An experiment is conducted to determine weather the average dose of vaccine exceeds that of another by .2 mg.
n1=45
n2=40
x1(bar) = #
x2(bar) = #
s1 = #
s1 =#
alpha/2 = 0.025
For this I used the ztest. Then question asks to test under same conditions, except that this time, n's are small and population variances are unknown. So how would I approach this?

I am closing this thread, I have just about given up on trying to find a solution to this problem.

what are the hypotheses?
It seems that you can either do the s pooled test if the pop variances are equal or the uequal case via Satterthwaite,
see Student's ttest  Wikipedia, the free encyclopedia
read...
Equal sample sizes, equal variance
This test is only used when both:
the two sample sizes (that is, the n or number of participants of each group) are equal;
it can be assumed that the two distributions have the same variance.
AND
Unequal sample sizes, equal variance