Wikipedia states that stochastic means random. But there are differences depending on the context.
Stochastic is used as an adjective, as in stochastic process, stochastic model, or stochastic simulation, with the meaning that phenomena as analyzed has an element of uncertainty or chance (random element). If a system is not stochastic, it is deterministic.
I may consider a phenomena is a random process and analyze it using a stochastic simulation model.
When we generate numbers using a probability distribution, these are called random numbers, or pseudo random numbers. They can also be called random deviates.
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These words are used to describe ways of modeling or understanding the world. "Stochastic" means that some elements of the model or description are thought of as being random. (The word "Stochastic" is derived from an ancient Greek word for random.) A model or description that has no random factors, but conceivably could, is called "deterministic." For example, the equation Q = VC where Q = charge, V = voltage, and C = capacitance, is a deterministic physical model. One stochastic version of it would be Q = VC + e where e is a random variable introduced to account for or characterize the deviations between the actual charges and the values predicted by the deterministic model.
Stochastic process is also known as a random process. It is a collection of random variables that represent the evolution of some system of random values over time.
monte carlo simulation is used to give solutions of deterministic problems whereas stochastic simulation is used for stochastic problems.
Stochastic testing is the same as "monkey testing", but stochastic testing is a lot more technical sounding name for the same testing process. Stochastic testing is black box testing, random testing, performed by automated testing tools. Stochastic testing is a series of random tests over time. The software under test typically passes the individual tests, but our goal is to see if it can pass a large number of individual tests.
Ah, the stochastic error term and the residual are like happy little clouds in our painting. The stochastic error term represents the random variability in our data that we can't explain, while the residual is the difference between the observed value and the predicted value by our model. Both are important in understanding and improving our models, just like adding details to our beautiful landscape.
A stochastic error indicates an error that is random between measurements. Stochastics typically occur through the sum of many random errors.
These words are used to describe ways of modeling or understanding the world. "Stochastic" means that some elements of the model or description are thought of as being random. (The word "Stochastic" is derived from an ancient Greek word for random.) A model or description that has no random factors, but conceivably could, is called "deterministic." For example, the equation Q = VC where Q = charge, V = voltage, and C = capacitance, is a deterministic physical model. One stochastic version of it would be Q = VC + e where e is a random variable introduced to account for or characterize the deviations between the actual charges and the values predicted by the deterministic model.
stochastic demand is random demand. it is determined by predictable actions and a random element.
Stochastic process is also known as a random process. It is a collection of random variables that represent the evolution of some system of random values over time.
monte carlo simulation is used to give solutions of deterministic problems whereas stochastic simulation is used for stochastic problems.
no, it is a random process
Stochastic processes are families of random variables. Real-valued (i.e., continuous) random variables are often defined by their (cumulative) distribution function.
A deterministic sequence - as opposed to a stochastic or random sequence.
A stochastic error is a type of random error that occurs in statistical models or experiments. It is caused by factors that are unpredictable or beyond the control of the researcher, leading to variability in the data. Stochastic errors can be minimized through larger sample sizes or by using statistical techniques to account for their presence in the analysis.
Stochastic testing is the same as "monkey testing", but stochastic testing is a lot more technical sounding name for the same testing process. Stochastic testing is black box testing, random testing, performed by automated testing tools. Stochastic testing is a series of random tests over time. The software under test typically passes the individual tests, but our goal is to see if it can pass a large number of individual tests.
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I don't know the answer I am looking for the answers too. :) I'm only 41.