The Scenario: Congratulations. You have just inherited your uncle's business, which is a clothing store. Although the business was successful, your uncle was a "seat of the pants" (pursuing effort, judgement based on personal experience rather than technological aids or formal theory) type of businessman. There was never any sales analysis conducted concerning, e.g. determining the effectiveness of promotional policies. You intend to analyze past sales data to gain insight into the business operations. Attached you will find a hard copy of an Excel file called PROJDATA.XLS. The data in this file corresponds to a random sample of 200 sales transactions that took place over the previous year. Because all transactions took place during the previous year and all transactions took place on Saturdays, on non-holiday weekends, you are confident that seasonal and cyclical effects are absent from the data. The Analysis: Based on this sample, you seek to answer the following questions: 1. Should you consider targeting males or females in your promotional policy? In answering this question, consider the following: a) Is the proportion of male and female shoppers significantly different? (=.05)| b) Is the average sale amount for males different than the average sales amount for females? (a=.05) 2. Should you be encouraging or discouraging credit card sales? In answering this question, consider the following: a) Is the proportion of credit and non-credit sales significantly different? (=.05) b) Is the average sale amount for credit sales different than the average sales amount for females? (=.05) 3. What is the lag effectiveness of the current advertising policy? In answering this question, consider the following: a) Is the number of sales that occur 0, 1, and 2 weeks after an advertisement significantly different? (=.05) b) Does the average amount of a sale differ 0, 1, and 2 weeks after an advertisement? (a=.05) 4. Do buy-one, get one free" and/or coupon promotions lead to larger sales? In answering this question, consider the following: a) Does the average amount of a sale differ by promotion type? (=.05) b) Which type of sale, if any, is largest? 5. Can multiple regression be used to "profile" a sale and determine whether a customer is spending more or less than anticipated, i.e. to predict the amount of a sale given the profile of a sale? a) To answer this question, conduct a regression analysis. b) How does the regression analysis support (or not support) your answers to part 1-4 above? What to do? Apply the statistical tools that you have learned in class, to the above question using Microsoft Excel as a tool. You may either: 1. Build your own solutions. This requires you to emulate the manual solution techniques that you have learned, building appropriate formulas in your spreadsheet, or 2. Where they exist, use the built-in functions provided by Excel.