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Provide answers to following problems in Excel, with one problem per tab.Chapter 2 #324M ANALYTICS: Textbooks This exercise requires research on how books are priced on the Internet. We will divide books into three broad categories: popular books, school books or textbooks, and recreational books. Some books may fall in two or even three of these categories. Motivation (a) If you were able to reduce the cost of the books that you buy each year by 5 or 10%, how much do you think you might be able to save in a year? Method (b) Create a data table of prices for the three types of books. You will compare prices of books at two Internet stores. Your data table will have four columns: one for the name of the book, one for the type of the book, and two more columns for the prices. (If you don’t have two Internet stores at which you usually shop, use amazon.com and barnesandnoble.com.) What types of data are these? (c) Identify five books of each type. These form the rows of the data table.Mechanics (d) Fill in your table from prices on the Web. Did you find the prices of the books that you started with, or did you have to change the choice of books to find the books at both stores? (e) Do your prices include costs for shipping and taxes, if any? Should they? Message (f) Summarize the price difference that you found for each of the three types of books. Describe any clear patterns you found. For example, if one store is always cheaper, then you have an easy recommendation. Alternatively, if one store is cheaper for textbooks but more expensive for popular books, you have a slightly more complex story to tell. Chapter 3 #594M ANALYTICS: Growth IndustriesThe U.S. Department of Commerce tracks the number of workers employed in various industries in the United States. It summarizes these data in the Statistical Abstract of the United States. This regularly appearing volume contains a rich collection of tables and charts that describe the country.The data shown in the following table appear in Table 620 in the 2012 edition, available online at http://www.census.gov. This table summarizes a categorical variable from each of two data tables. These categorical variables identify the type of industry that employs the worker. Each row in the underlying data tables represents an employee, either in 2000 or 2010.Industry 2000 2010Agriculture 2,464 2,206Construction 9,931 9,077Manufacturing 19,644 14,081Transportation 7,380 7,134Education 11,255 13,155Health 14,933 18,907Hospitality 11,186 12,530Retail trade 15,763 15,934Finance 9374 9350Professional services 13,649 15,253Each value shown in this frequency table is a rounded count given in thousands. For example, about 2,464,000 were employed in agriculture and related industries in 2000.Motivation(a) A firm that sells business insurance that covers the health of employees is interested in how it should allocate its sales force over the different industries. Why would this firm be interested in a table such as this?Method(b) What type of plot would you recommend to show the distribution of the workforce over industries in each year?(c) Management is particularly interested in knowing which industries have experienced the most growth in the number of employees. What graph do you recommend to show changes in the size of the workforce in the different industries?Mechanics(d) Prepare the chart that you chose in part (c). Explain the order you chose to show the categories.(e) How does the chart highlight industries that have smaller employment in 2000 than in 2010?(f) Do you think you should show all 10 categories, or should some rows be combined or set aside?Message(g) What message does your chart convey about the changing nature of employment?(h) By focusing on the growth and using a single chart, what’s hidden? Chapter 4 #644M ANALYTICS: Credit ScoresWhen a customer asks to borrow money, many banks check their credit score before giving them a loan. The credit score estimates the risk associated with making a loan to the customer. Credit scores are based on how well an individual has handled past debts. Customers that have made regular payments on time on several loans get a high score, whereas those who have been late and perhaps defaulted on a loan have lower scores.The data in this question give the credit score for 963 individuals who recently obtained small business loans from a lender. The average score is 580. The lender is considering raising its standards for getting a loan to reduce its exposure to losses. An executive proposed raising the minimum credit score for these loans to 550, saying that such a score would not lose too much business as it was ‘below average’.Motivation(a) The average of these credit scores is 580. Why would it be useful for managers of the lender to examine other attributes of the data before deciding on new standards?Method(b) What other attributes of the data should the managers examine?Mechanics(c) Present a display that captures the relevant attributes of these credit scores. Include relevant Message(d) What do you think of the recommended new credit limit? Chapter 5 #554M ANALYTICS: Discrimination in HiringContingency tables appear frequently in legal cases, such as those that allege that a company has discriminated against a protected class. The following table gives the number of employees of different ages who were laid off when a company anticipated a decline in business:1616 J. L. Gastwirth, “Statistical Evidence in Discrimination Cases,” Journal of the Royal Statistical Society, Series A 160(1997), 289–303. Laid Off Retained TotalAge < 40 18 787 80540–49 14 632 64650–59 18 374 39260 or more 18 107 125Several long-time employees who were laid off filed a suit against the company for wrongful termination. All were over 50, and they claimed the company discriminated on the basis of age.To use data like these in a trial requires a more complete analysis than we are ready to do. For now, we’ll settle for a descriptive analysis that lays the foundation.Motivation(a) From the employees’ point of view. On the basis of the claim of their lawsuit, would the laid-off employees expect to find association in this table?(b) From the company’s point of view. If the company does not discriminate on the basis of age, would you expect to find association in this table?Method(c) From either point of view. Would it be more useful to find the percentages within the columns or the percentages within the rows?(d) What statistic would you choose to represent the presence or absence of evidence of discrimination?Mechanics(e) Are age and employment status associated? Compute the appropriate summary statistic and interpret its value.Message(f) Summarize what you find in your analysis of the table.(g) How would the presence of a lurking factor compromise the use of data such as these in a legal case? Chapter 6 #554M ANALYTICS: Correlation in the Stock MarketApple, HP, IBM, and Microsoft are well known in the computer industry. If the computer industry is doing well, then we might expect the stocks of all four to increase in value. If the industry goes down, we’d expect all four to go down as well. How strong is the association among these companies? After all, they compete in some areas. For example, HP and IBM both sell powerful computer systems designed to power Web sites like Amazon or http://weather.com.This data set has monthly returns for Apple, HP, IBM, and Microsoft for January 1990 through December 2014. The returns are calculated as In this fraction, Pt is the price of the stock at the end of a month, and Pt − 1 denotes the price at the end of the prior month. If multiplied by 100, the return is the percentage change in the value of the stock during the month. The returns given here have been adjusted for accounting activities (such as dividend payments) that would otherwise produce misleading results. The data are from the Center for Research in Security Prices (CRSP).Motivation(a) Investors who buy stocks often buy several to avoid putting all their eggs into one basket. Why would someone who buys stocks care whether the returns for these stocks were related to each other?(b) Would investors who are concerned about putting all their eggs into one basket prefer to buy stocks that are positively related, unrelated, or negatively related?Method(c) How can an investor use correlations to determine whether these four stocks are related to each other? How many correlations are needed?(d) Correlations can be fooled by patterns that are not linear or distorted by outliers that do not conform to the usual pattern. Before using correlations, how can the investor check the conditions needed for using a correlation?(e) A key lurking variable anytime we look at a scatterplot of two time series is time itself. How can an investor check whether time is a lurking factor when looking at stock returns?Mechanics(f) Obtain the scatterplots needed to see whether there are patterns that relate the returns of these stocks. Does it matter which stock return goes on the x-axis and which goes on the y-axis? Do you find that the returns are associated? Is the association linear?(g) Obtain the correlation matrix that has all of the correlations among these four stocks.(h) Look at timeplots of the returns on each stock. Why are these important when looking at time series?Message(i) Summarize your analysis of the association among these returns for an investor who is thinking of buying these stocks. Be sure to talk about stocks, not correlations.

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