Asked by Jessica Braga on Jun 05, 2024

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Parsimony is where ________.

A) the model is kept as simple as possible
B) having as many variables as possible for accuracy
C) multiple models answer questions
D) none of the above

Parsimony

The principle of using the simplest or least complicated explanatory means necessary to adequately account for observed phenomena, often used in model selection.

  • Master the techniques and criteria necessary for the simplification and selection of models within multiple regression analysis.
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Sierra BakerJun 07, 2024
Final Answer :
A
Explanation :
Parsimony is about choosing the simplest explanation or model that fits the data. This helps to avoid overfitting or adding unnecessary complexity, which can lead to less accurate predictions or conclusions. Therefore, the best choice is A, where the model is kept as simple as possible. B and C would go against the principle of parsimony. D is incorrect because A is a valid choice.