a theoretical distribution of the number of trials required before the first success is obtained in a Bernoulli process (see
Bernoulli trial). Such a distribution is defined by two values: 0 and 1. Usually a value of 0 is used to denote a failure (i.e., the item of interest does not occur) and a value of 1 is used to denote a success (i.e., the item of interest does occur). On this basis, the likeliness of a success is denoted as
p and the likeliness of a failure is denoted as
q = 1 −
p. For example, a single toss of a coin has a Bernoulli distribution with
p = 0.5 (where 0 = heads and 1 = tails). A Bernoulli distribution is a special case of a
binomial distribution. [Jacques Bernoulli (1654–1705), Swiss mathematician and scientist]