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business
business statistics in practice

Business Statistics Plus Pearson Mylab Statistics With Pearson Etext 3rd Edition Norean R Sharpe ,Richard D De Veaux ,Paul Velleman - Solutions

=+a) The Durbin-Watson statistic for this analysis is 0.73.Consult Table D in Appendix B and complete the test at a = 0.05.
=+14. The regression of Total Revenue on Total Expenses for the concerts of Exercise 13 gives the following model:Dependent variable is: Total Revenue R squared = 56.4% R squared (adjusted) = 55.0%s = 24269 with 34 - 2 = 32 degrees of freedom Variable Coefficient SE(Coeff) t-ratio P-value Intercept
=+b) Specify what this statistic tests and what the test says about these data.
=+a) Consult Table D in Appendix B using k = 1 and n = 45 and complete the test at a = 0.05.
=+13. The manager of the concert production company considered in earlier exercises considers the regression of Total Revenue on Ticket Sales (see Exercise 4) and computes the Durbin-Watson statistic, obtaining a value of 0.51.
=+c) Is there evidence of negative autocorrelation? Explain.
=+b) Is there evidence of positive autocorrelation? Explain
=+12. An establishment specializing in mail order deliveries fits a regression to predict the number of mail orders over a period of 38 months. The Durbin-Watson statistic on residuals is 0.875.a) At a = 0.01, using k = 1 and n = 50, what are the values of dL and dU?
=+61. OECD GDP. The Organization for Economic Cooperation and Development (OECD) is an organization comprised of thirty countries. To belong, a country must support the principles of representative democracy and a free market economy. How have these countries grown in the decade from 1988 to
=+11. A beverage company specializing in sales of champagne reports four years of quarterly sales as follows (in millions of $):Quarter Sales ($M)1 12 2 41 3 15 4 48 5 25 6 55 7 23 8 69 9 51 10 80 11 54 12 87 13 64 14 94 15 62 16 108 The regression equation is Predicted Sales = 14.15 + 4.87
=+d) Does the new point have a large residual? Explain.Section 16.5
=+a) Find the regression line predicting Price from Capacity with this hard drive added.
=+d) Does the new point have a large residual? Explain.10. The data for hard drives in Exercise 6 originally included a 200 GB (0.2 TB) drive that sold for $299.00 (see Chapter 4, Exercise 2).
=+c) Is the new point a high leverage point or an influential point?
=+b) What has changed from the original regression equation?
=+a) Find the regression line predicting Sales from Number of people working with the new point added.
=+9. The bookstore in Exercise 5 decides to have a gala event in an attempt to drum up business. They hire 100 employees for the day and bring in a total of $42,000.
=+One performer refused to permit advanced sales. What effect has that point had on the regression to model Total Revenue from Advanced Sales?Section 16.3
=+8. The production company of Exercise 7 offers advanced sales to “Frequent Buyers” through its website. Here’s a relevant scatterplot:160,000 80,000 120,000 40,000 Total Revenue 0.0 7.5 15.0 22.5 30.0 Advanced Sales
=+b) Why would it be a poor business decision to assume that this model accurately predicts revenue for this situation?
=+a) Management is considering adding a stadium-style venue that would seat 10,000. What does this model predict that revenue would be if the new venue were to sell out?
=+7. A regression of Total Revenue on Ticket Sales by the concert production company of Exercises 2 and 4 finds the model Revenue = -14,228 + 36.87 TicketSales
=+a) Disk drives keep growing in capacity. Some tech experts now talk about Petabyte 1PB = 1000 TB = 1,000,000 GB2 drives. What does this model predict that a Petabytecapacity drive will cost?b) Is this prediction likely to be useful? Explain.M16_SHAR8696_03_SE_C16.indd 569 14/07/14 7:37 AM 570
=+6. Here are prices for the external disk drives we saw in Chapter 15, Exercise 10:Capacity (in TB) Price (in $)0.15 35.00 0.25 39.95 0.32 49.95 1.0 75.00 2.0 110.00 3.0 140.00 4.0 325.00 x = 1.53 y = 110.7 SD1x2 = 1.515 SD1y2 = 102.049 The least squares line is Price = 15.11 + 62.417 Capacity.The
=+a) Find the predicted sales on a day with 500 employees working.b) Is this prediction likely to be useful? Explain.
=+60. Life expectancy. Life insurance rates are based on life expectancy values compiled for large demographic groups.But with improvements in medical care and nutrition, life expectancies have been changing. Here is a table from the National Vital Statistics Report that gives the Life Expectancy
=+5. Here are the data from the small bookstore we saw in Chapter 15, Exercise 9.Number of Sales People Working Sales (in $1000)2 10 3 11 7 13 9 14 10 18 10 20 12 20 15 22 16 22 20 26 x = 10.4 y = 17.6 SD1x2 = 5.64 SD1y2 = 5.34 The regression line is:Sales = 8.10 + 0.913 Number of Sales People
=+a) Describe the relationship between Ticket Sales and Total Revenue.
=+4. The concert production company of Exercise 2 made a second scatterplot, this time relating Total Revenue to Ticket Sales.160,000 80,000 120,000 40,000 Total Revenue 750 1500 2250 3000 Ticket Sales
=+3. The analyst in Exercise 1 tried fitting the regression line to each market segment separately and found the following:1000 2000 3000 4000 5000 6000 7000 December 8000 7000 6000 5000 4000 3000 2000 1000 0January 0What does this say about her concern in Exercise 1?Was she justified in worrying
=+c) How are they different?
=+b) How are the results for the two venues similar?
=+a) Describe the relationship between Talent Cost and Total Revenue. (Remember: direction, form, strength, outliers.)
=+2. A concert production company examined its records.The manager made the following scatterplot. The company places concerts in two venues, a smaller, more intimate theater (plotted with blue circles) and a larger auditorium-style venue.160,000 80,000 120,000 40,000 Total Revenue 25,000 50,000
=+Another analyst worried that different types of cardholders might behave differently. She examined the spending patterns of the cardholders and placed them into five market Segments. When she plotted the data using different colors and symbols for the five different segments, she found the
=+An analysis of spending by a sample of credit card bank cardholders shows that spending by cardholders in January(Jan) is related to their spending in December (Dec):0 1000 2000 3000 4000 5000 6000 December 8000 6000 4000 2000 0January The assumptions and conditions of the linear regression
=+• Propose an ethical solution that considers the welfare of all stakeholders
=+• What are the undesirable consequences?
=+• Identify the ethical dilemma in this scenario.
=+Which of these does the best job of making the relationship linear? Does the plot indicate that we have satisfied the regression assumptions?
=+Why should we check the Durbin-Watson statistic for this analysis? What does the statistic say about these data?
=+What would be the effect of including these exotic diamonds on regression lines fit to each of these scatterplots?
=+ Do you think this model should be relied on to establish prices for large diamonds?
=+c) What does this model suggest about logs 36 inches in diameter?
=+What does this model predict for the Price of the Cullinan I diamond? Is the estimate of $400 million consistent with this model?
=+a) The number of licensed lobster fishers has fluctuated over the years between roughly 5000 and 10,000. Recently the number has been just over 7000. But licenses are in demand(and tightly restricted). What does this model predict the value of the catch would be in a year if there were 10,000
=+How does the relationship of Price and Carat Weight change with Color?
=+55. Lobsters 2012, part 3. Here’s a regression model relating the logValue of the annual Maine lobster catch to the number of licensed lobster Fishers since 1985:Dependent variable is: LogValue R squared = 17.6%s = 0.2752 with 28 - 2 = 26 degrees of freedom Variable Coefficient SE(Coeff)
=+d) Can you use the regression model to help in your understanding of the growth of this market?
=+c) What features of the residuals might be dealt with by a re-expression? Which ones would not be helped by a re-expression?
=+b) What features of the residuals should be noted with regards to this regression?
=+a) What does the R2 value in the regression mean?
=+48. Home Depot sales. The home retail industry experienced relatively consistent annual growth until the economic crisis of 2006. Here is a scatterplot of the Net Sales ($B) of The Home Depot from 1995 through 2004, along with a regression and a time series plot of the residuals.20 16 12 84
=+b) Would a re-expression help us deal with this pattern?Explain.
=+a) Can you account for the pattern shown here?
=+47. Oakland passengers, part 2. In Exercise 29, we created a linear model describing the trend in the number of passengers departing from Oakland (CA) airport each month since the start of 1997. Here’s the residual plot, but with lines added to show the order of the values in time: Residuals
=+. Residuals, part 2. Suppose you have fit a linear model to some data and now take a look at the residuals. For each of the following possible residuals plots, tell whether you would try a re-expression and, if so, why.a)b) c)
=+49. Models. For each of the models listed below, predict y when x = 4.a) yn = 3.6 + 0.6xb) ln y = 3.6 + 0.6xc) 1y = 3.6 + 0.6xd) 1>y = 3.6 + 0.6xe) yn = 3.6x0.6
=+50. More models. For each of the models listed below, predict y when x = 4.a) yn = 3.6 + 0.6xb) log yn = 3.6 + 0.6xc) yn = 3.6 + 0.61xd) yn = 3.610.6x 2e) yn = 0.6x2 + 3.6x + 2
=+51. Models, again. Find the predicted value of y, using x = 5 for each model.a) yn = 3 + 5 ln xb) log y = 4 - 0.45xc) 1 1yn = 17 - 2.67x
=+b) What can you see in the plots of residuals that may not have been clear in the original scatterplot of the data?
=+a) Does this plot satisfy the regression assumptions and conditions? Explain.A regression of Traps/Fisher vs. Year yields the following plot of residuals:40 0–30 1950.0 1962.5 1975.0 Year 30 1987.5 2000.0 Residuals
=+54. Lobsters 2012, part 2. Lobster are caught in traps, which are baited and left in the open ocean. Licenses to fish for lobster are limited, there is a small additional fee for each trap in use, and there are limits on the numbers of traps that can be placed in each of seven fishing zones. But
=+c) Discuss what this plot shows. Would a different transformation be likely to do better than the log? Explain.
=+After performing a regression on the log values, we obtain the following plot of residuals:0.187 0.112 0.037–0.038 Residuals 1950.0 1970.0 1990.0 2010.0 Year
=+b) Discuss the same assumptions as in parta. Does taking logs make these data suitable for regression?M16_SHAR8696_03_SE_C16.indd 578 14/07/14 7:38 AM Exercises 579
=+a) Which regression assumptions and conditions appear to be violated according to this plot?Here’s a scatterplot of the log of the value:8.3 7.9 7.5 7.1 6.7 Log10 Value 1950.0 1970.0 Year 1990.0 2010.0
=+53. Lobsters 2012. According to the Maine Department of Marine Resources, in 2012 more than 126,000,000 pounds of lobster were landed in Maine—a catch worth more than$338.9M. The lobster fishing industry is carefully controlled and licensed, and facts about it have been recorded for more than
=+52. Models, last time. Find the predicted value of y for each model when x = 3.a) yn = 2 + 1xb) 1 yn = 4 - 0.12xc) 1yn = 3 + 0.24x
=+45. Residuals. Suppose you have fit a linear model to some data and now take a look at the residuals. For each of the following possible residuals plots, tell whether you would try a re-expression and, if so, why.a)b) c)
=+56. Economic growth, revisited. The U.S. Bureau of Economic Analysis provides information on the GDP in the United States by metropolitan area (www.bea.gov). The Bureau recently released figures that showed the percent change in real GDP by metropolitan area for 2004–2005.Using the data in the
=+Highest Quintile Fourth Quintile Lowest Quintile Second Quintile Third Quintile MA 2.9 NJ 2.9 DC 4.1 DE 3.3 MD 2.9 RI 1.8 CT 2.6 AK 0.7 GDP % Change Top 40% Bottom 60% Total West (Far West, Southwest, and Rocky Mtn.)13 2 15 Midwest (Great Lakes and Plains States)2 10 12 Southeast 4 8 12
=+D.C is included in the Mideast Region.)GA 3.4 UT 7.2 CO 4.9 ID 7.4 HI 4.3 Far West U.S. Bureau of Economic Analysis NY MI 3.4–0.5 PA OH 1.7 1.1 VA 3.2 SC AL 3.5 3.1 MS 2.5 LA 1.7 NM 6.2 AZ 6.8 CA 4.2 NV 4.1 WY 2.2 MT 4.6 SD 3.7 ND 3.1 MN 2.9 WI 1.8 IA 2.6 NE 2.2 KS 3.4 OK 6.7 AR 2.5 MO 2.1 IL
=+55. Economic growth. The U.S. Bureau of Economic Analysis also provides information on the growth of the U.S.economy (www.bea.gov). The Bureau recently released figures that they claimed showed a growth spurt in the western region of the United States. Using the table and map below, determine if
=+54. U.S. Gross Domestic Product. The U.S. Bureau of Economic Analysis provides information on the Gross Domestic Product (GDP) in the United States by state (www.bea.gov). The Bureau recently released figures that showed the real GDP by state for 2007. Using the data in the table below examine
=+53. Information systems. In a recent study of enterprise resource planning (ERP) system effectiveness, researchers asked companies about how they assessed the success of their ERP systems. Out of 335 manufacturing companies surveyed, they found that 201 used return on investment(ROI), 100 used
=+b) Calculate and examine the standardized residuals. What pattern (if any, do they show that would be of interest to retailers concerned about cybershopping comparisons?
=+a) Is the frequency of comparison shopping on the Internet independent of the income level of the respondent?Perform an appropriate chi-square test and state your conclusion.
=+52. CyberShopping. It has become more common for shoppers to “comparison shop” using the Internet. Respondents to a Pew survey in 2013 who owned cell phones were asked whether they had, in the past 30 days, looked up the price of a product while they were in a store to see if they could get
=+51. Businesses and blogs. The Pew Internet & American Life Project routinely conducts surveys to gauge the impact of the Internet and technology on daily life. A recent survey asked respondents if they read online journals or blogs, an Internet activity of potential interest to many businesses.
=+5 experienced double-digit job growth, 16 had single-digit growth, and 9 had no growth or job loss. Ignoring Google, is job growth in the best of the best places to work different from job growth in the bottom of that elite list?a) Select the appropriate procedure.b) Check the assumptions.c)
=+50. Ranking companies. Every year, Fortune Magazine lists the 100 best companies to work for, based on criteria such as pay, benefits, turnover rate, and diversity. In 2013, the top three were Google, SAS, and CHG Healthcare. Of the top 30, 11 experienced double-digit job growth (10%or more), 16,
=+e) Interpret the meaning of the results and state a conclusion.
=+49. Management styles. Use the survey results in the table below to investigate differences in employee job satisfaction among organizations in the United States with different management styles.Employee Job Satisfaction Very Satisfied Satisfied Somewhat Satisfied Not Satisfied Management
=+e) Interpret the meaning of the results and state the conclusion.
=+48. Industry sector and outsourcing, part 2. Consider only the companies that have outsourced their IT and HR business segments. Do these data suggest significant differences between companies in the financial and industrial goods sectors with regard to their outsourcing decisions? Industry
=+d) Test an appropriate hypothesis and state your results.e) Interpret the meaning of the results and state a conclusion.
=+b) Check the assumptions.c) State the hypotheses.
=+(HR). The data below show the types of outsourcing decisions made (no outsourcing, IT only, HR only, both IT and HR) by a sample of companies from various industry sectors.NoOutsourcing IT Only HR Only Both IT and HR Industry Sector Health Care 810 6429 4725 1127 Financial 263 1598 549 117
=+47. Industry sector and outsourcing. Many companies have chosen to outsource segments of their business to external providers in order to cut costs and improve quality and/or efficiencies. Common business segments that are outsourced include Information Technology (IT) and Human Resources
=+46. Titanic, one more time. Find a 95% confidence interval for the difference in the proportion of women who survived and the proportion of men who survived for the data in Exercise 44. (Assume the passengers on the Titanic were representative of others who might have taken the trip.)
=+45. Racial steering, revisited. Find a 95% confidence interval for the difference in the proportions of Black renters in the two sections for the data in Exercise 43.
=+44. Titanic, again. Newspaper headlines at the time and traditional wisdom in the succeeding decades have held that women and children escaped the Titanic in greater proportion than men. Here’s a table with the relevant data. Do you think that survival was independent of whether the person was
=+43. Racial steering. A subtle form of racial discrimination in housing is “racial steering.” Racial steering occurs when real estate agents show prospective buyers only homes in neighborhoods already dominated by that family’s race.This violates the Fair Housing Act of 1968. Tenants at a
=+e) With this change in the table, what has happened to the number of degrees of freedom?f) Test your hypothesis about the two groups and state an appropriate conclusion.
=+d) Create a new table by combining categories so that a chi-square procedure can be used.
=+c) Find the expected counts for each cell and explain why chi-square procedures are not appropriate for this table.
=+b) Write the appropriate hypotheses.M14_SHAR8696_03_SE_C14.indd 502 14/07/14 7:30 AM Exercises 503
=+a) Will you test goodness-of-fit, homogeneity, or independence?
=+42. Small business. The director of a small business development center located in a mid-sized city is reviewing data about its clients. In particular, she is interested in examining if the distribution of business owners across the various stages of the business life cycle is the same for

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