In a number of statistics books and references you can find formulas such as:
$P\,(result~|~H_0)$ (Bortz, p. 114)
$P\,(reject~H_0\;|\;H_0~valid)$ (Wikipedia - Statistical hypothesis testing)
and you will probably find many others if you just google for 'hypothesis testing'.
Isn't this abusing the notation of $P$ and / or mixing two very different things into $P$?
My point is, if we talk about some result $R$ (e.g., the sequence $(0, 1, 1, 1, 1, 0, 1)$ of coin flips) over some space $\Omega$, then $P(R)$ is very well defined and clear to me.
However, $P(H_0)$ (which as I understand it is to be interpreted as "the probability that $H_0$ is true") must be from some totally unrelated meta-space $\Omega_{realworld}$ and the only thing I could relate it to would be the probability space over all possible probability spaces for $P$.
How can / does writing something like $P\,(R~|~H_0)$ make sense? How can I 'reason' with it? How could I apply, for example, Bayes' theorem?