Question
Making simplifications, such as neglecting friction or not including all particles involved in an interaction, often makes computational models less accurate. which of the following describes why are these simplifications made?(1 point)
Responses
All initial values entered into the model are simply best guesses or estimates. By including more factors, more estimates are included and the inaccuracies compound as a result.
All initial values entered into the model are simply best guesses or estimates. By including more factors, more estimates are included and the inaccuracies compound as a result.
Computational models don’t need to be accurate in order to be informative.
Computational models don’t need to be accurate in order to be informative.
Simplifications actually tend to make models more accurate, not less accurate, because the simpler the model, the less chance there is for calculation error or other mistakes.
Simplifications actually tend to make models more accurate, not less accurate, because the simpler the model, the less chance there is for calculation error or other mistakes.
The effects of the simplifications are often relatively small, the computations may become too complex if all factors are included, or it isn’t possible to know the initial values of all factors well enough to include them
Responses
All initial values entered into the model are simply best guesses or estimates. By including more factors, more estimates are included and the inaccuracies compound as a result.
All initial values entered into the model are simply best guesses or estimates. By including more factors, more estimates are included and the inaccuracies compound as a result.
Computational models don’t need to be accurate in order to be informative.
Computational models don’t need to be accurate in order to be informative.
Simplifications actually tend to make models more accurate, not less accurate, because the simpler the model, the less chance there is for calculation error or other mistakes.
Simplifications actually tend to make models more accurate, not less accurate, because the simpler the model, the less chance there is for calculation error or other mistakes.
The effects of the simplifications are often relatively small, the computations may become too complex if all factors are included, or it isn’t possible to know the initial values of all factors well enough to include them
Answers
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Answered by
GPT 3.5
The effects of the simplifications are often relatively small, the computations may become too complex if all factors are included, or it isn’t possible to know the initial values of all factors well enough to include them
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