 Effect algebras exist in great abundance. In particular, if \(\Omega\) is a convex set arising as the state-space of a probabilistic model, then the set \({\mathcal E}(\Omega)\) of bounded affine (convex-linear) functions \(f : \Omega \rightarrow [0,1]\) form an effect algebra, with \(f \oplus g = f + g\) if \(f + g \leq 1\).  The idea is that a function \(\,f \in {\mathcal E}(\Omega)\) represents an "in principle" measurement outcome, with probability \(f(\alpha)\) in state \(\alpha \in \Omega\).  If \(f_0,...,f_n \in {\mathcal E}(\Omega)\) with \(f_0 + \cdots + f_n = 1\), then the sequence \((f_0,...,f_n)\) rpresents an “in principle” observable with values \(i = 0,...,n\), taking value \(i\) with probability \(f_i(\alpha)\).