While trying to answer this question, I've come across the notion of the weak*-topology on a set of probability measures. I'd like some clarification about what this means.
More specifically, let $(\Omega, \mathcal{F})$ be a measurable space. We don't assume that $\Omega$ has any metric or topological structure. What does it mean to equip the set $\mathcal{M}$ of probability measures on this space with the weak*-star topology?
I understand that the weak*-topology is the weakest topology on the dual space $V'$ of a normed vector space $V$ that makes the evaluation functionals defined by $\lambda_f(\phi) = \phi(f)$, $\phi \in V'$ and $f \in V$, continuous. What I don't understand is how $\mathcal{M}$ can be equipped with this topology as it's not a vector space.
From what I've read, I think that measures in $\mathcal{M}$ are being identified with linear functionals on a space of measurable functions. For instance, $P \in \mathcal{M}$ gives rise to a linear functional $\phi$ on the normed linear space of bounded $\mathcal{F}$-measurable functions, equipped with the $\sup$-norm, by $\phi(f) := \int f dP$. Is something like this correct? Which underlying vector space of measurable functions should be used?
I would appreciate if someone could please sketch the relevant theory for me and/or refer me to a comprehensive textbook treatment of this topic.
Addendum. My current understanding of this topic is summarized as part of my attempt to answer my own question in the link above.