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1. Of, relating to, or characterized by conjecture; conjectural.
2. Statistics Involving or containing a random variable or process: stochastic calculus; a stochastic simulation.

[Greek stokhastikos, from stokhastēs, diviner, from stokhazesthai, to guess at, from stokhos, aim, goal; see stegh- in Indo-European roots.]

sto·chas′ti·cal·ly adv.


1. (Statistics) statistics
a. (of a random variable) having a probability distribution, usually with finite variance
b. (of a process) involving a random variable the successive values of which are not independent
c. (of a matrix) square with non-negative elements that add to unity in each row
2. rare involving conjecture
[C17: from Greek stokhastikos capable of guessing, from stokhazesthai to aim at, conjecture, from stokhos a target]
stoˈchastically adv


(stəˈkæs tɪk)

adj. Statistics.
of or pertaining to a process involving a randomly determined sequence of observations each of which is considered as a sample of one element from a probability distribution.
[1655–65; < Greek stochastikós proceeding by conjecture =stochas(tḗs) diviner (stochad-, base of stocházesthai to aim at + -tēs agent suffix) + -ikos -ic]
sto•chas′ti•cal•ly, adv.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Adj.1.stochastic - being or having a random variable; "a stochastic variable"; "stochastic processes"
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
random - lacking any definite plan or order or purpose; governed by or depending on chance; "a random choice"; "bombs fell at random"; "random movements"
References in periodicals archive ?
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of Helsinki, Finland) can be a viewed as self-contained, together they are intended as a "coherent and rigorous treatment of uncertainty and its implications for describing relevant stochastic processes through basic (prototype, core) models and differential equations of stochastic dynamics.
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With applications, examples and accessible text this covers such background material as Brownian motions and Martingales, stochastic integrals and stochastic differential equations, then moves to scalar equations of first order, stochastic parabolic equations, stochastic parabolic equations in the whole space, stochastic hyperbolic equations, stochastic evolution equations in Hilbert spaces, asymptotic behaviors of solutions, further applications such as random Schrodinger equations and nonlinear stochastic beam equations and diffusion equations in infinite dimensions.