When selecting a regression model in a complicated situation, which of the following statements is FALSE?

Question $1$ options:

In a model with a predictive goal, coefficient significance is relatively more important than overall model fit.

Practical and legal constraints matter when selecting models in business situations.

There is no best model.

A model which violates regression conditions, when non$-$violating models are possible with about the same overall strength, is a poor model.