You work for a financial services company that is trying to promote their new personal wealth management service to their customers. The service is quite costly to promote to customers, and few customers are signing up for the service, making it imperative that you do an effective job of promoting the service to the customers who are most likely to want it. You run a test campaign with a random sample of 1000 customers. The following represents results from a binary logistic regression predicting whether or not these customers signed up for the service. The model is based on the number of years the customer has been with us (Lifetime), gender (females coded as 1), the net worth of the household in thousands of dollars (NetWorth), and the size of the household (HHS). Use these results to answer the following five questions: w... x2 5...... - _I------ l-----m SE mm Use this table to answer the following questions. Show and explain all your work. 1. Which variables are statistically significant predictors of signing up using a 0.05 alpha level? 2. Interpret the unstandardized coefficient estimate for the NetWorth variable. 3. Are men or women more likely to sign up for the service? 4. According to the results, which variable has the greatest relative effect on response probability? 5. Identify and interpret the odds ratio for the NetWorth variable. Consider a male consumer having a household of size 3, a household net worth of $95,000, and a lifetime of 3 years. What is the predicted probability of this customer signing up? What are his odds? Suppose the customer in problem 5 had 2 more years of customer lifetime with no other changes? What are his odds of response now