In probability theory, a Poisson process is a stochastic process which counts the number of events and the time that these events occur in a given time interval. The time between each pair of consecutive events has an exponential distribution with parameter λ and each of these inter-arrival times is assumed to be independent of other inter-arrival times. The process is named after the French mathematician Siméon-Denis Poisson and is a good model of radioactive decay, telephone calls and requests for a particular document on a web server, among many other phenomena.
The Poisson process is a continuous-time process; the sum of a Bernoulli process can be thought of as its discrete-time counterpart. A Poisson process is a pure-birth process, the simplest example of a birth-death process. It is also a point process on the real half-line.
Read more about Poisson Process: Definition, Characterisation, Properties, Applications, Occurrence
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“Any balance we achieve between adult and parental identities, between children’s and our own needs, works only for a time—because, as one father says, “It’s a new ball game just about every week.” So we are always in the process of learning to be parents.”
—Joan Sheingold Ditzion, Dennie, and Palmer Wolf. Ourselves and Our Children, by Boston Women’s Health Book Collective, ch. 2 (1978)