  In animal groups, individual decisions are best characterised by
probabilistic rules. Furthermore, animals of many species live in small groups.
Probabilistic interactions among small numbers of individuals lead to a so
called intrinsic noise at the group level. Theory predicts that the strength of
intrinsic noise is not a constant but often depends on the collective state of
the group; hence, it is also called a state-dependent noise or a multiplicative
noise. Surprisingly, such noise may produce collective order. However, only a
few empirical studies on collective behaviour have paid attention to such
effects due to the lack of methods that enable us to connect data with theory.
Here, we demonstrate a method to characterise the role of stochasticity
directly from high-resolution time-series data of collective dynamics. We do
this by employing two well-studied individual-based toy models of collective
behaviour. We argue that the group-level noise may encode important information
about the underlying processes at the individual scale. In summary, we describe
a method that enables us to establish connections between empirical data of
animal (or cellular) collectives with the phenomenon of noise-induced states, a
field that is otherwise largely limited to the theoretical literature.
