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A '''stochastic process''' is a [[probability|probabilistic]] model of a system that evolves non-deterministically.<ref>c.f. {{cite book | author=Kulkarni, V. G. | title=Modeling and Analysis of Stochastic Systems| publisher=Chapman & Hall | year=1995 | editor= | id=ISBN 0-412-04991-0}}</ref>

A '''stochastic process''' is a [[probability|probabilistic]] model of a system that evolves non-deterministically.<ref>c.f. {{cite book | author=Kulkarni, V. G. | title=Modeling and Analysis of Stochastic Systems| publisher=Chapman & Hall | year=1995 | editor= | id=ISBN 0-412-04991-0}}</ref> Statisticians determine the system by approximating a [[probability distribution]], which assigns a level of certainty to particular evolutions. When the probability is high, evolution will likely occur; when it is low, so is the likelihood of evolution. Statisticians often model stochastic processes by using [[Markov chain]]s, [[Monte Carlo analysis]], [[Poisson distribution]]s, [[kinematics]] and [[cellular automata]]. Stochastic processes are used in varied fields such as [[demography]], [[ekistics]], [[geology]], [[nuclear]] [[physics]], [[astrology]], and [[paleontology]].

==References==

==References==