You are given data on a sample of 200 customers of Apollo, a (fictional) direct marketing company, for the current year. The variables are defined as follows: Person = a code for the customer Age = a code for the age category, 1 = 30 or younger, 2 = if 31 to 55, 3 if 56 or older Gender = 1 if male, 0 if female Own Home = 1 if customer owns home, 0 if renting Married = 1 if married, 0 if not Close = 1 if lives close to stores (with similar merchandise), 0 if not Salary = annual household salary in $ Children = number of children living with this customer Catalogs = number of catalogs this customer was sent this year (6, 12, 18 or 24) Region = region in the US where the customer lives State = state where the customer lives Amount Spent = Amount spent total on purchases this year (a) Create a PivotTable with rows = Gender, columns = Salary, and values = average of amount spent. In addition, group the Salary values in increments of 20,000, i e., the column labels should be: 0-19999, 20000-39999, etc. (b) Overall, does the average amount spent increase or decrease with the salary? Is the trend the same for both male and female? (c) Create another PivotTable, this time with rows = Region, columns = Close, and values = average of amount spent. (d) From either PivotTable, determine the average amount customers spend. (You should get the same answer from either table.) From (c), answer (e) and (f). (e) Customers in which region tend to spend the most? (f) Who spends more at Apollo? The people who live close to stores with similar merchandise or the people who don't? (g) Now make 2 copies of this Pivot Table. Filter the new Pivot Tables such that one contains only the homeowners' data and the other contains only the non-homeowners' data. (h) On the average, do the homeowners spend more or less than non-homeowners? Support your answer with numbers