A university is applying classification methods in order to identify alumni who may be interested in donating money. The university has a database of 58,205 alumni profiles containing numerous variables. Of these 58,205 alumni, only 576 have donated in the past. The university has oversampled the data and trained a random forest of 100 classification trees. For a cutoff value of 0.5, the following confusion matrix summarizes the performance of the random forest on a validation set: 

The following table lists some information on individual observations from the validation set.

a. Explain how the Probability of Donation was computed for the three observations.
Why were Observations A and C classified as Donation and Observation B was classified as No Donation?

b. Compute the values of accuracy, sensitivity, specificity, and precision. Explain why accuracy is a misleading measure to consider in this case. Evaluate the performance of the random forest, particularly commenting on the precision measure.

Actual Donation Donation 268 No Donation 5375 Predicted No Donation 20 23,439