A stochastic process is a probabilistic model of a system that evolves non-deterministically. 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 chains, Monte Carlo analysis, Poisson distributions, kinematics and cellular automata. Stochastic processes are used in varied fields such as demography, ekistics, geology, nuclear physics, astrology, and paleontology.
- c.f. Kulkarni, V. G. (1995). Modeling and Analysis of Stochastic Systems. Chapman & Hall. ISBN 0-412-04991-0.