The above questions are necessary when it comes to modelling description under the methodology section.
In the context of modeling, the terms "stochastic model," "probabilistic model," and "deterministic model" have specific meanings and differences:
In summary, the main difference between stochastic and probabilistic models is that stochastic models introduce randomness or uncertainty into the modeling process, while probabilistic models specifically use probability distributions to quantify and predict outcomes. On the other hand, deterministic models do not account for randomness and assume that outcomes are entirely predictable based on known inputs and equations. It's important to choose the appropriate type of model based on the nature of the system being studied and the level of uncertainty or randomness involved.
That is very interesting. I really appreciate your intellectual response in this regard. Thanks a lot to you and all other respondents to this question.
I think that Chakit Arora provides a good way of defining those three terms. However, I would caution against assuming that those definitions are applied consistently across different fields of study.
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