What does stochastic mean?

Definitions for stochastic
stəˈkæs tɪksto·chas·tic

Here are all the possible meanings and translations of the word stochastic.

Princeton's WordNet

  1. stochasticadjective

    being or having a random variable

    "a stochastic variable"; "stochastic processes"

GCIDE

  1. Stochasticadjective

    (Statistics) of or pertaining to a process in which a series of calculations, selections, or observations are made, each one being randomly determined as a sample from a probability distribution. Where physical phenomena are modelled as a stochastic process, each subsequent calculation of a series may depend on the result of the previous calculation, as in the modelling of the process of diffusion of molecules. Many series may be calculated, and the results averaged, to estimate the most likely result. See also Markov chain.

    Etymology: [Gr. stochastiko`s, from stocha`zesqai to aim, to guess, fr. sto`chos mark or aim.]

Wiktionary

  1. stochasticadjective

    Random, randomly determined, relating to stochastics.

Webster Dictionary

  1. Stochasticadjective

    conjectural; able to conjecture

    Etymology: [Gr. stochastiko`s, from stocha`zesqai to aim, to guess, fr. sto`chos mark or aim.]

Freebase

  1. Stochastic

    In probability theory, a stochastic system is one whose state is non-deterministic. The subsequent state of a stochastic system is determined both by the system's predictable actions and by a random element. A stochastic process is one whose behavior is non-deterministic; it can be thought of as a sequence of random variables. Any system or process that can be analyzed using probability theory is stochastic. Stochastic systems and processes play a fundamental role in mathematical models of phenomena in many fields of science, engineering, and economics. Stochastic comes from the Greek word στόχος, which means "aim". It also denotes a target stick; the pattern of arrows around a target stick stuck in a hillside is representative of what is stochastic.

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Numerology

  1. Chaldean Numerology

    The numerical value of stochastic in Chaldean Numerology is: 7

  2. Pythagorean Numerology

    The numerical value of stochastic in Pythagorean Numerology is: 9

Examples of stochastic in a Sentence

  1. Reza Sanaye:

    Basics of Macro-systems' Behavior Prediction 1 .The Macro-systems with their sometimes stochastic behavior may be (good) indicators of the dispersal of information from a holistic standpoint as well as [to be discussed later on] from a regionally molecular anisotropic zone. 2. The data scattering as for systems with quasi-vector behavior on liquids, on gases, and amongst solids, when observed from an epi-phenomenological perspective versus a phenomenological one, can show that a number of classical views on mechanistic behavior of Macro-systems may be substituted with some “machinic” view.¬ 3. The abandonment of the purely mechanistic view of interfacial forces and the adoption of thermodynamic and probabilistic concepts such as free energy and entropy have been two of the most important steps towards getting out of the worn-out mechanistic notions into more abstract conceptualization of information dispersal, working instead of causality. 4. Comparison also has to be made between hermeneutics of the notion of entropic forces within and without the framework of established thermodynamics. The very word “force” is itself a bit too collocated with entropy already. What we are after is to make it next of kin to ideas of data, information, topology of data, and mereology of stochasticity. 5. The physico-chemical potentiality inside a variety of equilibrium states can be used as a platform for anisotropic configurations whereby not only the entropy of confinement, but also the entropy of dispersal find their true meaning. 6. Within contexts of classical accumulation and energy-growth models, the verifiability of any anisotropic reversal is also demonstrable, if not by means of a set of axioms, at least by multiplicities of interfacial behavior in which experimental data find their mereotopological ratios one in the neighborhood of the other (considering first, for the sake of simplicity, our state spaces to be of metric nature). 7. Thus, there remains the reciprocity of interfacial tensions calculations where surface tension gives rise to internal polarization of those data systems by which we should like to derive either axiomatic or multiple manifoldic regionalization of PREDICTION. 8. This, with a number of Chaotic and Strange-Attractors modifications, can potentially be applied even to the whole matrix of the Universe. 9. Most of the literature on systems (information) entropy regard mesoscopic level as THE one with highest aptitude for (physicalistic) data analysis. However, there are clues to indicate that some of the main streams of structuration and dynamics are EITHER in common amongst microscopic, mesoscopic, and macroscopic systems OR holistic patterns of the said structurations and dynamics can be derived one from the other two. For example, we shall show later—in the course of the unfolding of present notions—that density functional theory (DFT) which has become the physicists’ methodology for describing solids’ electronic structure, can also be extended to other methods or systems. Few-atom systems can implicate the already explicated order of, say, biomolecules if rigorous analyses are carried out over the transition phases (translational data mappings). 10. The level of likelihood of information dispersal in any nano- and pico-systems with/without (full) attachment to and/or dependence upon chemical energy exchange, relates to dynamics of differentials of those multiplicities of tubing interconnector manifolds which potentially have the capacity to harness thermal energy. This spells that consumption of chemical energy does not necessarily always act against the infusion of energy. Here, delineation has to be made over the minutiae of the differences between Micro- and Macro-systems. Any movement of lines of demarcation throughout the said systems over the issue of (non-)interdependency of data mereotopology on chemical energy exchange, may be predicted if classical nucleation and growth theories give their place to an even more rigorous science of Differences. Repetition of (observation) of such Differences makes it possible to see through some of the most “macro” levels of systematicity [we have already run some simulations of micro-spaces’ state mappings for purposes of clarifying how many of the plasma macro jet streams inside stars or in the inter-galaxial space move. Even magneticity has turned out, with all due caution, to be comparable]. The above-said Differences actually refer to potentialities within lines of thermodynamic exchanges based upon anisotropy of information. Such exchanges nominate themselves as MO exchanges when “micro” but as some the most specific gravito-convectional currents in usages for astrology, earth science, and ecology. Thence, the science will be brought out of prognosing the detailed balance of mesoscopic (ir-)reversibility in terms of data neighborhoods connectivity. On any differentiable manifold with its own ring of universal differentiable functions, we may determine to have the “installing” of modules of Kähler spaces where demarcation could be represented by: d(a+b)=da+db, d(ab)=adb+bda, and: dλ=0(a,b∈A,λ∈k)d(a+b)=da+db,d(ab)=adb+bda,dλ=0(a,b∈A,λ∈k) Where any one module has the formalism: dbdb (b∈Ab∈A). All these having been said, again we have the problematics of still remaining within the realm of classic calculus. It is likely that for Macrosystems we may decide not to apply the classical version.

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    easily diffused or spread as from one person to another
    • A. contiguous
    • B. foreordained
    • C. eloquent
    • D. contagious

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