So, this may be a common question, but I’ve never found a satisfactory answer.  

How do you determine the probability that the null hypothesis is true (or false)?

Let’s say you give students two different versions of a test and want to see if the versions were equivalent.  You perform a t-Test and it gives a p-value of .02.  What a nice p-value!  That must mean it’s unlikely that the tests are equivalent, right?  No.  Unfortunately, it appears that P(results|null) doesn’t tell you P(null|results).  The normal thing to do is to reject the null hypothesis when we encounter a low p-value, but how do we know that we are not rejecting a null hypothesis that is very likely true?  To give a silly example, I can design a test for ebola with a false positive rate of .02: put 50 balls in a bucket and write “ebola” on one.  If I test someone with this and they pick the “ebola” ball, the p-value (P(picking the ball|they don’t have ebola)) is .02, but I definitely shouldn’t reject the null hypothesis that they are ebola-free.  

Things I’ve considered so far:

1.	Assuming P(null|results)~=P(results|null) – clearly false for some important applications.
2.	Accept or reject hypothesis without knowing P(null|results) – Why are we accepting or rejecting them then?  Isn’t the whole point that we reject what we think is LIKELY false and accept what is LIKELY true?
3.	Use Bayes’ Theorem – But how do you get your priors?  Don’t you end up back in the same place trying to determine them experimentally?  And picking them a priori seems very arbitrary.  
4.	I found a very similar question here: stats.stackexchange.com/questions/231580/. The one answer here seems to basically say that it doesn't make sense to ask about the probability of a null hypothesis being true since that's a Bayesian question.  Maybe I'm a Bayesian at heart, but I can't imagine not asking that question.  In fact, it seems that the most common misunderstanding of p-values is that they are the probability of a true null hypothesis.  If you really can't ask this question as a frequentist, then my main question is #3: how do you get your priors without getting stuck in a loop?