The above development takes a random process, the Bernoulli process, and converts it to a measure-preserving dynamical system formula_76 The same conversion (equivalence, isomorphism) can be applied to any stochastic process. Thus, an informal definition of ergodicity is that a sequence is ergodic if it visits all of formula_2; such sequences are "typical" for the process. Another is that its statistical properties can be deduced from a single, sufficiently long, random sample of the process (thus uniformly sampling all of formula_2), or that any collection of random samples from a process must represent the average statistical properties of the entire process (that is, samples drawn uniformly from formula_2 are representative of formula_2 as a whole.) In the present example, a sequence of coin flips, where half are heads, and half are tails, is a "typical" sequence.