Multiple Choice Questions '1. The predicted purchase probability calculated from a regression is equal to which of the following values calculated using pivot tables? a) Antecedent b) Consequent 0) Support d) Condence e) Lift 2. Which of these best describes a residual? a) It must be a number between 0 and 1 b) It must be positive c) It must be negative d) It must have both positive and negative values e) It represents a distance between observed and predicted values 3. The graph that shows Cumulative % of buyers vs customer rank is designed to: a) See how good our model is at predicting customer purchase b) See how many people purchased c) See which people purchased d) Identify the people that are most and least likely to purchase e) Compare our model to random targeting