Models are usually approximations, too simple and sometimes unrealistic.
Explanation:
A model is an abstraction of the real world. Models are used by scientists to mimic and gain better insights into how the real world looks like to a greater degree of accuracy. Here are some set backs of models;
- Limitations due to parameters that can be modeled; it is nearly impossible to incorporate all the elements of the real world into a model. A scientist may have limited resources to integrate different data sets to perfectly have a good picture of the real world.
- Models are approximations: the fact that models are not exact can be worrisome. Questions like to what extent are these scenarios rounded can be very difficult to come by with and this can spoil a good research.
- Over simplicity: most times when a model proves too complex to work with, some parameters are left out and this can cause a good model to be watered and not portray the real world at all.
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