Amarketing manager wants to predict customers with the risk of churning (switching their service contracts to another company), based on the number of calls the customer makes to the company call center and the number of visits the customer makes to the local service center. data from a random sample of 30 customers show that 15 have churned (coded as "1") and 15 have not churned (coded as"o") develop a logistic regression model to predict the probability of churn based on the number of calls the customer makes to the company call center and the number of visits the customer makes to the local service center a phstat output yield that bo-1.6023, bi0.061953023, b2- 0.094175407, si0.0291, sb20.5214, zstai 2.1316, zstat2 0.1806, and zcritical 1.96. also, deviance-30.13249138, andriical a) predict the probability of churn for a customer who called the com- pany called the call center 10 times and visited the local service center once. b) at the 5% level of significance, is this a good-fitting model? c) at the 5% level of significance, do the number of calls to the call center as well as the number of visits to the local service station, individually make a significant contribution to the model?