The file P3_83.XLS contains data on 1000 of Marvak’s best customers. Marvak is a directmarketing firm that sells electronic items. It has collected these data to learn more about its customers. The variables are self-explanatory, although a few cell notes have been added in row 3. Your boss at Marvak would like you, the Excel guru, to do the following.

a. She wants a breakdown of gender by age group. That is, she wants a pivot table that lists, for each age group, the percentages of females and males. She wants to be able to access this information easily (with a couple of clicks) for any subcategories of Home and Married.

b. She guesses that customers with larger salaries tend to spend more at Marvak. To check this, she wants you to append a new variable called SalaryCat to the data set that contains the four category labels in column J. A customer with salary below $30,000 is categorized as “LowSal”; between $30,000 and $70,000 as ‘“MedSal”; between $70,000 and $120,000 as “HighSal”; and over $120,000 as “HugeSal.” (By the way, no incomes are exactly equal to $30,000, $70,000, or $120,000.) You can use the lookup table in columns I and J to form this new SalaryCat column. Then create a pivot table that shows the average amount spent for each of the four salary categories, and comment briefly (on that sheet) whether your boss’s conjecture appears to be correct.