Please answer and explain question 1 to 5 in exercise 2 using the display 4.8 (sas enterprise miner) please explain thoughroughly

Exercise 2 An auto insurance company has developed a decision tree model in order to classify the prospective customers as likely responders and non-responders. The target variable is RESP I. The decision tree assigns all customers who have income less than $25,000 and Age greater tha or equal to 35 years to the Leaf Node 1. The decision tree also calculated the posterior probabilities as P and P . These posterior probabilities indicate that the probability that a customer who is assigned to the Leaf Node I will respond to a solicitation to apply for auto insurance is P0.02 and the probability that the customer will not respond is P -0.98 Given the posterior probabilities given in Step I and using the 2. profit matrix shown in Display 48 ify the customers who belong to Leaf Node 1 as Responders or Non-responders (Hint Compare the expected profits under Decision 1 and Decision 2, where Decision I means the customers in Leaf Nodel as responders and Decision 2 means labeling them as non- responders.) labeling 3. After applying the decision tree to the test data set, it is found that 200 customers in set ended up in Leaf Node 1. Of these 200 customers, 6 were found to be actual rep 194 customers were non-responders. the Test data responders and 4. Suppose you apply the decision tree model and score a Prospect data set. Ifa custome e scored data set is randomly selected and is assigned to Leaf Node 1 by the Decision e then what is the predicted probability that the customer will respond to an invitatior auto insurance? model Tree to apply for Given the decision you arrived at in Step 2, would you send an invitation to the ou in Step 4 to apply for auto insurance? Why or why not? 5. customer selected