  For example, if a sequence is genuinely random, we should expect that in the long run it would tend to have features we associate with the outputs of (independent, identically distributed trials of) a chancy process. The sequence should look as disorderly as if it were the expected product of genuine chance. This approach is known accordingly as the typicality approach to randomness. Typicality is normally defined with respect to a prior probability function, since what is a typical series of fair coin toss outcomes might not be a typical series of unfair coin toss outcomes (Eagle 2016: 447). In the present case, we use the Lebesgue measure as it is the natural measure definable from the symmetries of the outcome space of the binary process itself.  