Precision and Recall, key metrics for classification model evaluation, assess positive prediction accuracy (Precision) and the capture of all true positive instances (Recall). The F1 score, the harmonic mean of Precision and Recall, reaches 1 when both components are 1, not 0. Therefore, Statement 1 is accurate, and Statement 2 is inaccurate.