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bayesian statistics an introduction
Statistics For Business And Economics 14th Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran, Michael J. Fry, Jeffrey W. Ohlmann - Solutions
6. Emergency Facilities and Distance to Service. A study of emergency service facilities investigated the relationship between the number of facilities and the average distance traveled to provide the emergency service. The following table gives the data collected.Number of Average Distance
5. Curvilinear Relationship Between Vehicle Speed and Traffic Flow. In working further with the problem of exercise 4, statisticians suggested the use of the following curvilinear estimated regression equation.yˆ 5 b0 1 b1x 1 b2x2a. Use the data of exercise 4 to estimate the parameters of this
4. Vehicle Speed and Traffic Flow. A highway department is studying the relationship between traffic flow and speed. The following model has been hypothesized.y 5 b0 1 b1x 1 e where y 5 x 5 traffic flow in vehicles per hour vehicle speed in kilometers per hour The following data were collected
3. Consider the following data for two variables, x and y.x 2 3 4 5 7 7 7 8 9 y 4 5 4 6 4 6 9 5 11a. Does there appear to be a linear relationship between x and y? Explain.b. Develop the estimated regression equation relating x and y.c. Plot the standardized residuals versus yˆ for the estimated
2. Consider the following data for two variables, x and y.x 9 32 18 15 26 y 10 20 21 16 22a. Develop an estimated regression equation for the data of the form yˆ = b0 + b1x.Comment on the adequacy of this equation for predicting y.b. Develop an estimated regression equation for the data of the
1. Consider the following data for two variables, x and y.x 22 24 26 30 35 40 y 12 21 33 35 40 36a. Develop an estimated regression equation for the data of the form yˆ = b0 + b1x.b. Use the results from part (a) to test for a significant relationship between x and y.Use a = .05.c. Develop a
57. Gift Card Sales. For the holiday season of 2017, nearly 59 percent of consumers planned to buy gift cards. According to the National Retail Federation, millennials like to purchase gift cards (Dayton Daily News website). Consider the sample data in the file GiftCards. The following data are
56. Mutual Fund Returns. A portion of a data set containing information for 45 mutual funds that are part of the Morningstar Funds 500 follows. The complete data set is available in the file named MutualFunds. The data set includes the following five variables:Fund Type: The type of fund, labeled
55. Zoo Attendance. The Cincinnati Zoo and Botanical Gardens had a record attendance of 1.87 million visitors in 2017 (Cincinnati Business Courier website). Nonprofit organizations such as zoos and museums are becoming more sophisticated in their use of data to improve the customer experience.
54. Analyzing Repeat Purchases. The Tire Rack, America’s leading online distributor of tires and wheels, conducts extensive testing to provide customers with products that are right for their vehicle, driving style, and driving conditions. In addition, the Tire Rack maintains an independent
53. Analyzing Job Satisfaction. Recall that in exercise 50 the personnel director for Electronics Associates developed the following estimated regression equation relating an employee’s score on a job satisfaction test to length of service and wage rate.yˆ 5 14.41 2 8.69x1 1 13.52x2 where x1 5
52. Analyzing College Grade Point Average. Recall that in exercise 49, the admissions officer for Clearwater College developed the following estimated regression equation relating final college GPA to the student’s SAT mathe matics score and high-school GPA.yˆ 5 21.41 1 .0235x1 1 .00486x2 where
51. A partial computer output from a regression analysis follows.The regression equation is Y = 8.13 + 7.602 XI + 3.111 X2 Predictor Coef SE Coef T Constant _______ 2.667 _____ X1 _______ 2.105 _____ X2 _______ 0.613 _____ S = 3.335 R-Sq = 92.3% R-Sq (adj) = _____%Analysis of Variance SouRCE DF SS
50. Job Satisfaction. The personnel director for Electronics Associates developed the following estimated regression equation relating an employee’s score on a job satisfaction test to his or her length of service and wage rate.yˆ 5 14.4 2 8.69x1 1 13.5x2 where x1 5 x2 5 y 5 length of service
49. College Grade Point Average. The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student’s SAT mathematics score and high-school GPA.yˆ 5 21.41 1 .0235x1 1 .00486x2 where x1 5 x2 5 y 5 high-school grade
48. Repeat Sales. The Tire Rack maintains an independent consumer survey to help drivers help each other by sharing their long-term tire experiences. The data contained in the file named TireRatings show survey results for 68 all-season tires. Performance traits are rated using the following
47. College Retention. Over the past few years the percentage of students who leave Lakeland College at the end of the first year has increased. Last year Lakeland started a voluntary one-week orientation program to help first-year students adjust to campus life.If Lakeland is able to show that the
46. Direct Deposit. Community Bank would like to increase the number of customers who use payroll direct deposit. Management is considering a new sales campaign that will require each branch manager to call each customer who does not currently use payroll direct deposit. As an incentive to sign up
45. Odds Ratio for Coupon Redemption. In Table 15.12 we provided estimates of the probability of using the coupon in the Simmons Stores catalog promotion. A different value is obtained for each combination of values for the independent variables.a. Compute the odds in favor of using the coupon for
44. Coupon Redemption. Refer to the Simmons Stores example introduced in this section. The dependent variable is coded as y = 1 if the customer used the coupon and 0 if not. Suppose that the only information available to help predict whether the customer will use the coupon is the customer’s
43. Golf Scores. The Ladies Professional Golfers Association (LPGA) maintains statistics on performance and earnings for members of the LPGA Tour. Year-end performance statistics for 134 golfers for 2014 appear in the file named LPGA2014 (LPGA website, April 2015). Earnings ($1000s) is the total
42. Sports Car Prices. The following data show the curb weight, horsepower, and 400-meter speed for 16 popular sports and GT cars. Suppose that the price of each sports and GT car is also available. The complete data set is as follows:Sports & GT Car Price ($1000s)Curb Weight (kg) Horsepower Speed
41. Detecting Outliers in Theater Revenue. Exercise 5 gave the following data on weekly gross revenue, television advertising, and newspaper advertising for Showtime Movie Theaters.Weekly Gross Revenue ($1000s)Television Advertising ($1000s)Newspaper Advertising ($1000s)96 5.0 1.5 90 2.0 2.0 95 4.0
40. Data for two variables, x and y, follow.xi 22 24 26 28 40 yi 12 21 31 35 70a. Develop the estimated regression equation for these data.b. Compute the studentized deleted residuals for these data. At the .05 level of significance, can any of these observations be classified as an outlier?
39. Data for two variables, x and y, follow.xi 1 2 3 4 5 yi 3 7 5 11 14a. Develop the estimated regression equation for these data.b. Plot the standardized residuals versus yˆ. Do there appear to be any outliers in these data? Explain.c. Compute the studentized deleted residuals for these data. At
38. Risk of a Stroke. A 10-year study conducted by the American Heart Association provided data on how age, blood pressure, and smoking relate to the risk of strokes. Assume that the following data are from a portion of this study. Risk is interpreted as the probability (times 100) that the patient
37. Pricing Refrigerators. Best Buy, a nationwide retailer of electronics, computers, and appliances, sells several brands of refrigerators. A random sample of models of full size refrigerators prices sold by Best Buy and the corresponding capacity in liters and list price follow (Best Buy
36. Extending Model for Repair Time. This problem is an extension of the situation described in exercise 35.a. Develop the estimated regression equation to predict the repair time given the number of months since the last maintenance service, the type of repair, and the repairperson who performed
35. Repair Time. Refer to the Johnson Filtration problem introduced in this section. Suppose that in addition to information on the number of months since the machine was serviced and whether a mechanical or an electrical repair was necessary, the managers obtained a list showing which repairperson
34. Fast Food Sales. Management proposed the following regression model to predict sales at a fast-food outlet.y 5 b0 1 b1x1 1 b2 x2 1 b3 x3 1 e where x1 = number of competitors within one kilometer x2 = population within one kilometer (1000s)x3 5 51 if drive-up window present 0 otherwise y = sales
33. Consider a regression study involving a dependent variable y, a quantitative independent variable x1, and a categorical independent variable with three possible levels (level 1, level 2, and level 3).a. How many dummy variables are required to represent the categorical variable?b. Write a
32. Consider a regression study involving a dependent variable y, a quantitative independent variable x1, and a categorical independent variable with two levels(level 1 and level 2).a. Write a multiple regression equation relating x1 and the categorical variable to y.b. What is the expected value
31. Confidence and Prediction Intervals for Auto Resale Value. Refer to Problem 25.Use the estimated regression equation from part (a) to answer the following questions.a. Estimate the selling price of a four-year-old Honda Accord with mileage of 65,000 kilometers.b. Develop a 95% confidence
30. Confidence and Prediction Intervals for NFL Wins. In exercise 24, an estimated regression equation was developed relating the percentage of games won by a team in the National Football League for the 2011 season given the average number of passing yards obtained per game on offense and the
29. Confidence and Prediction Intervals for Theater Revenue. In exercise 5, the owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (x2).The estimated regression equation was
28. Refer to the data in exercise 2. The estimated regression equation for those data is yˆ 5 218.4 1 2.01x1 1 4.74x2a. Develop a 95% confidence interval for the mean value of y when x1 = 47 and x2 = 10.b. Develop a 95% prediction interval for y when x1 = 47 and x2 = 10.
27. In exercise 1, the following estimated regression equation based on 10 observations was presented.yˆ 5 29.1270 1 .5906x1 1 .4980x2a. Develop a point estimate of the mean value of y when x1 = 180 and x2 = 310.b. Develop a point estimate for an individual value of y when x1 = 180 and x2 = 310.
26. Testing Significance in Baseball Pitcher Performance. In exercise 10, data showing the values of several pitching statistics for a random sample of 20 pitchers from the American League of Major League Baseball were provided. In part (c) of this exercise an estimated regression equation was
25. Auto Resale Value. The Honda Accord was named the best midsized car for resale value for 2018 by the Kelley Blue Book (Kelley Blue Book website). The file AutoResale contains mileage, age, and selling price for a sample of 33 Honda Accords.a. Develop an estimated regression equation that
24. Testing Significance in Predicting NFL Wins. The National Football League (NFL)records a variety of performance data for individuals and teams. A portion of the data showing the average number of passing yards obtained per game on offense (Off-PassYds/G), the average number of yards given up
23. Testing Significance in Theater Revenue. Refer to exercise 5.a. Use a = .01 to test the hypotheses H0:Ha:b1 5 b2 5 0 b1 and/or b2 is not equal to zero for the model y = b0 + b1x1 + b2x2 +e, where x1 5 x2 5 television advertising ($1000s)newspaper advertising ($1000s)b. Use a = .05 to test the
22. Testing Significance in Shoe Sales Prediction. In exercise 4, the following estimated regression equation relating sales to inventory investment and advertising expenditures was given.yˆ 5 25 1 10x1 1 8x2 The data used to develop the model came from a survey of 10 stores; for these data SST =
21. The following estimated regression equation was developed for a model involving two independent variables.yˆ 5 40.7 1 8.63x1 1 2.71x2 After x2 was dropped from the model, the least squares method was used to obtain an estimated regression equation involving only x1 as an independent
20. Refer to the data presented in exercise 2. The estimated regression equation for these data is yˆ 5 218.37 1 2.01x1 1 4.74x2 Here SST = 15,182.9, SSR = 14,052.2, sb1= .2471, and sb2= .9484.a. Test for a significant relationship among x1, x2, and y. Use a = .05.b. Is b1 significant? Use a =
19. In exercise 1, the following estimated regression equation based on 10 observations was presented.yˆ 5 29.1270 1 .5906x1 1 .4980x2 Here SST = 6724.125, SSR = 6216.375, sb1= .0813, and sb2= .0567.a. Compute MSR and MSE.b. Compute F and perform the appropriate F test. Use a = .05.c. Perform a t
18. R2 in Predicting Baseball Pitcher Performance. Refer to exercise 10, where Major League Baseball (MLB) pitching statistics were reported for a random sample of 20 pitchers from the American League for one full season.a. In part (c) of exercise 10, an estimated regression equation was developed
17. Quality of Fit in Predicting House Prices. Revisit exercise 9, where we develop an estimated regression equation that can be used to predict the selling price given the number of bathrooms, square meterage, and number of bedrooms in the house.a. Does the estimated regression equation provide a
16. Quality of Fit in Predicting NFL Wins. In exercise 6, data were given on the average number of passing yards per attempt (Yds/Att), the number of interceptions thrown per attempt (Int/Att), and the percentage of games won (Win%) for a random sample of 16 National Football League (NFL) teams for
15. R2 in Theater Revenue Prediction. In exercise 5, the owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue ( y) as a function of television advertising (x1) and newspaper advertising (x2). The estimated regression equation was yˆ 5 83.2 1 2.29x1 1
14. R2 in Shoe Sales Prediction. In exercise 4, the following estimated regression equation relating sales to inventory investment and advertising expenditures was given.yˆ 5 25 1 10x1 1 8x2 The data used to develop the model came from a survey of 10 stores; for those data, SST = 16,000 and SSR =
13. In exercise 3, the following estimated regression equation based on 30 observations was presented.yˆ 5 17.6 1 3.8x1 2 2.3x2 1 7.6x3 1 2.7x4 The values of SST and SSR are 1805 and 1760, respectively.a. Compute R2.b. Compute R2a.c. Comment on the goodness of fit.
12. In exercise 2, 10 observations were provided for a dependent variable y and two independent variables x1 and x2; for these data SST = 15,182.9, and SSR = 14,052.2.a. Compute R2.b. Compute R2a.c. Does the estimated regression equation explain a large amount of the variability in the data?
11. In exercise 1, the following estimated regression equation based on 10 observations was presented.yˆ 5 29.1270 1 .5906x1 1 .4980x2 The values of SST and SSR are 6724.125 and 6216.375, respectively.a. Find SSE.b. Compute R2.c. Compute R2a.d. Comment on the goodness of fit.
10. Baseball Pitcher Performance. Major League Baseball (MLB) consists of teams that play in the American League and the National League. MLB collects a wide variety of team and player statistics. Some of the statistics often used to evaluate pitching performance are as follows:ERA: The average
9. House Prices. Spring is a peak time for selling houses. The file SpringHouses contains the selling price, number of bathrooms, square meterage, and number of bedrooms of 26 homes sold in Ft. Thomas, Kentucky, in spring 2018 (realtor.com website).a. Develop scatter plots of selling price versus
8. Scoring Cruise Ships. The Condé Nast Traveler Gold List provides ratings for the top 20 small cruise ships. The data shown below are the scores each ship received based upon the results from Condé Nast Traveler’s annual Readers’ Choice Survey.Each score represents the percentage of
7. Rating Computer Monitors. PC Magazine provided ratings for several characteristics of computer monitors, including an overall rating (PC Magazine website). The following data show the rating for contrast ratio, resolution, and the overall rating for ten monitors tested using a 0–100 point
6. NFL Winning Percentage. The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the conference(Conf), average number of passing yards per attempt
5. Theater Revenue. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow.Weekly Television Newspaper Gross Revenue Advertising Advertising($1000s) ($1000s) ($1000s)96 5.0
4. Shoe Sales. A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures.yˆ 5 25 1 10x1 1 8x 2 where x1 5 x2 5 y 5 inventory investment ($1000s)advertising expenditures ($1000s)sales ($1000s)a. Predict the sales resulting
3. In a regression analysis involving 30 observations, the following estimated regression equation was obtained.yˆ 5 17.6 1 3.8x1 2 2.3x 2 1 7.6x3 1 2.7x4a. Interpret b1, b2, b3, and b4 in this estimated regression equation.b. Predict y when x1 = 10, x2 = 5, x3 = 1, and x4 = 2.
2. Consider the following data for a dependent variable y and two independent variables, x1 and x2.x1 x2 y 30 12 94 47 10 108 25 17 112 51 16 178 40 5 94 51 19 175 74 7 170 36 12 117 59 13 142 76 16 211a. Develop an estimated regression equation relating y to x1. Predict y if x1 = 47.b. Develop an
1. The estimated regression equation for a model involving two independent variables and 10 observations follows.yˆ 5 29.1270 1 .5906x1 1 .4980x 2a. Interpret b1 and b2 in this estimated regression equation.b. Predict y when x1 = 180 and x2 = 310.
68. Used Car Mileage and Price. The Toyota Camry is one of the best-selling cars in North America. The cost of a previously owned Camry depends upon many factors, including the model year, mileage, and condition. To investigate the relationship between the car’s mileage and the sales price for a
67. Income and Percent Audited. The Transactional Records Access Clearinghouse at Syracuse University reported data showing the odds of an Internal Revenue Service audit. The following table shows the average adjusted gross income reported and the percent of the returns that were audited for 20
66. Market Beta. Market betas for individual stocks are determined by simple linear regression. For each stock, the dependent variable is its quarterly percentage return(capital appreciation plus dividends) minus the percentage return that could be obtained from a risk-free investment (the Treasury
65. Studying and Grades. A marketing professor at Givens College is interested in the relationship between hours spent studying and total points earned in a course. Data collected on 10 students who took the course last quarter follow.Hours Total Spent Studying Points Earned 45 40 30 35 90 75 60 65
64. Bus Maintenance. The regional transit authority for a major metropolitan area wants to determine whether there is any relationship between the age of a bus and the annual maintenance cost. A sample of 10 buses resulted in the following data.Age of Bus (years) Maintenance Cost ($)1 350 2 370 2
63. Absenteeism and Location. A sociologist was hired by a large city hospital to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (kilometers) between home and work for the employees. A sample of 10 employees was chosen, and
62. Production Rate and Quality Control. In a manufacturing process the assembly line speed (meters per minute) was thought to affect the number of defective parts found during the inspection process. To test this theory, managers devised a situation in which the same batch of parts was inspected
61. Machine Maintenance. Jensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenance expense should be related to usage,and they collected the following information on weekly
60. Online Education. One of the biggest changes in higher education in recent years has been the growth of online universities. The Online Education Database is an independent organization whose mission is to build a comprehensive list of the top accredited online colleges. The following table
59. Home Size and Price. Is the number of square meters of living space a good predictor of a house’s selling price? The following data collected in April, 2015, show the square meterage and selling price for fifteen houses in Winston Salem, North Carolina (Zillow.com).Size (sq. m)Selling Price
58. Stock Market Performance. The Dow Jones Industrial Average (DJIA) and the Standard & Poor’s 500 (S&P 500) indexes are used as measures of overall movement in the stock market. The DJIA is based on the price movements of 30 large companies; the S&P 500 is an index composed of 500 stocks. Some
57. What is the purpose of testing whether b1 = 0? If we reject b1 = 0, does it imply a good fit?
56. In your own words, explain the difference between an interval estimate of the mean value of y for a given x and an interval estimate for an individual value of y for a given x.
54. Valuation of a Major League Baseball Team. The following data show the annual revenue ($ millions) and the estimated team value ($ millions) for 30 Major League Baseball teams (Forbes website).Team Revenue ($ millions) Value ($ millions)Arizona Diamondbacks 195 584 Atlanta Braves 225 629
53. Supermarket Checkout Lines. Retail chain Kroger has more than 2700 locations and is the largest supermarket in the United States based on revenue. Kroger has invested heavily in data, technology, and analytics. Feeding predictive models with data from an infrared sensor system called QueVision
51. Consider the following data for two variables, x and y.xi 4 5 7 8 10 12 12 22 yi 12 14 16 15 18 20 24 19a. Compute the standardized residuals for these data. Do the data include any outliers?Explain.b. Compute the leverage values for these data. Do there appear to be any influential
50. Consider the following data for two variables, x and y.xi 135 110 130 145 175 160 120 yi 145 100 120 120 130 130 110a. Compute the standardized residuals for these data. Do the data include any outliers?Explain.b. Plot the standardized residuals against yˆ. Does this plot reveal any
49. Buy Versus Rent. Occasionally, it has been the case that home prices and mortgage rates dropped so low that in a number of cities the monthly cost of owning a home was less expensive than renting. The following data show the average asking rent for 10 markets and the monthly mortgage on the
48. Experience and Sales. Refer to exercise 7, where an estimated regression equation relating years of experience and annual sales was developed.a. Compute the residuals and construct a residual plot for this problem.b. Do the assumptions about the error terms seem reasonable in light of the
47. Restaurant Advertising and Revenue. Data on advertising expenditures and revenue(in thousands of dollars) for the Four Seasons Restaurant follow.Advertising Expenditures Revenue 1 19 2 32 4 44 6 40 10 52 14 53 20 54a. Let x equal advertising expenditures and y equal revenue. Use the method of
46. The following data were used in a regression study.Observation xi yi Observation xi yi 1 2 4 6 7 6 2 3 5 7 7 9 3 4 4 8 8 5 4 5 6 9 9 11 5 7 4a. Develop an estimated regression equation for these data.b. Construct a plot of the residuals. Do the assumptions about the error term seem to be
45. Given are data for two variables, x and y.xi 6 11 15 18 20 yi 6 8 12 20 30a. Develop an estimated regression equation for these data.b. Compute the residuals.c. Develop a plot of the residuals against the independent variable x. Do the assumptions about the error terms seem to be satisfied?d.
44. Auto Racing Helmet. Automobile racing, high-performance driving schools, and driver education programs run by automobile clubs continue to grow in popularity. All these activities require the participant to wear a helmet that is certified by the Snell Memorial Foundation, a not-for-profit
43. Estimating Setup Time. Sherry is a production manager for a small manufacturing shop and is interested in developing a predictive model to estimate the time to produce an order of a given size—that is, the total time to produce a certain quantity of the product. She has collected data on the
42. Annual Sales and Salesforce. A regression model relating x, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following computer output from a regression analysis of the data.Analysis of Variance SOURCE DF Adj SS Adj MS Regression
41. Computer Maintenance. Following is a portion of the computer output for a regression analysis relating y = maintenance expense (dollars per month) to x = usage(hours per week) of a particular brand of computer.Analysis of Variance SOURCE DF Adj SS Adj MS Regression 1 1575.76 1575.76 Error 8
40. Apartment Selling Price. The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several
39. Entertainment Spend. The Wall Street Journal asked Concur Technologies, Inc., an expense-management company, to examine data from 8.3 million expense reports to provide insights regarding business travel expenses. Their analysis of the data showed that New York was the most expensive city. The
38. Prediction Intervals for Cost Estimation. Refer to exercise 21, where data on the production volume x and total cost y for a particu lar manufacturing operation were used to develop the estimated regression equation yˆ = 1246.67 + 7.6x.a. The company’s production schedule shows that 500
37. Auditing Itemized Deductions. In exercise 13, data were given on the adjusted gross income x and the amount of itemized deductions taken by taxpayers. Data were reported in thousands of dollars. With the estimated regression equation yˆ = 4.68 + .16x, the point estimate of a reasonable level
36. Sales Performance. In exercise 7, the data on y = annual sales ($1000s) for new customer accounts and x = number of years of experience for a sample of 10 salespersons provided the estimated regression equation yˆ = 80 + 4x. For these data x = 7, o(xi − x)2 = 142, and s = 4.6098.a. Develop a
35. Restaurant Lines. Many small restaurants in Portland, Oregon, and other cities across the United States do not take reservations. Owners say that with smaller capacity, no-shows are costly, and they would rather have their staff focused on customer service rather than maintaining a reservation
34. The data from exercise 3 follow.xi 2 6 9 13 20 yi 7 18 9 26 23 Develop the 95% confidence and prediction intervals when x = 12. Explain why these two intervals are different.
33. The data from exercise 2 follow.xi 3 12 6 20 14 yi 55 40 55 10 15a. Estimate the standard deviation of yˆ* when x = 8.b. Develop a 95% confidence interval for the expected value of y when x = 8.c. Estimate the standard deviation of an individual value of y when x = 8.d. Develop a 95%
32. The data from exercise 1 follow.xi 1 2 3 4 5 yi 3 7 5 11 14a. Use equation (14.23) to estimate the standard deviation of yˆ* when x = 4.b. Use expression (14.24) to develop a 95% confidence interval for the expected value of y when x = 4.c. Use equation (14.26) to estimate the standard
31. Significance of Racing Bike Weight on Price. In exercise 20, data on x = weight(kilograms) and y = price ($) for 10 road-racing bikes provided the estimated regression equation yˆ = 28,942 − 3213x. (Bicycling website). For these data SSE =6,735,080 and SST = 52,120,800. Use the F test to
30. Significance of Fleet Size on Rental Car Revenue. Companies in the U.S. car rental market vary greatly in terms of the size of the fleet, the number of locations, and annual revenue. The following data were used to investigate the relationship between the number of cars in service (1000s) and
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