  This paper presents an introduction to the stochastic concepts of
\emph{coupling} and \emph{copula}. Coupling means the construction of a joint
distribution of two or more random variables that need not be defined on one
and the same probability space, whereas a copula is a function that joins a
multivariate distribution to its one-dimensional margins. Their role in
stochastic modeling is illustrated by examples from multisensory perception.
Pointers to more advanced and recent treatments are provided.
