Which statement about the differences in using linear regression in the two scenarios of explanatory vs. predictive modeling is FALSE? A. A good explanatory model is one that fits the data as closely as possible, whereas a good predictive model is one that predicts new cases accurately. B. In explanatory models, the data set is partitioned into training and validation sets, whereas in predictive modeling the entire data set is used to build a model and assess the goodness of fit of the model. C. In explanatory models, the focus is on testing the statistical significance of coefficients that represent hypothesized relationships between pairs of variables. D. Regression can be used for both explanatory and predictive purposes