a. Develop a scatter diagram for these data.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Try to approximate the relationship between x and y by drawing a straight line through the data.
d. Develop the estimated regression equation by computing the values of b0 and b1 using equations (12.6) and (12.7).
e. Use the estimated regression equation to predict the value of y when x = 4.
Get solution
14.2 Given are five observations for two variables, x and y....
a. Develop a scatter diagram for these data.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Try to approximate the relationship between x and y by drawing a straight line through the data.
d. Develop the estimated regression equation by computing the values of b0 and b1 using equations (12.6) and (12.7).
e. Use the estimated regression equation to predict the value of y when x = 10.
Get solution
14.3 Given are five observations collected in a regression study on two variables....
a. Develop a scatter diagram for these data.
b. Develop the estimated regression equation for these data.
c. Use the estimated regression equation to predict the value of y when x = 6.
Get solution
14.4 The following data give the percentage of women working in five companies in the retail and trade industry. The percentage of management jobs held by women in each company is also shown....
a. Develop a scatter diagram for these data with the percentage of women working in the company as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Try to approximate the relationship between the percentage of women working in the company and the percentage of management jobs held by women in that company.
d. Develop the estimated regression equation by computing the values of b0 and b1.
e. Predict the percentage of management jobs held by women in a company that has 60% women employees.
Get solution
14.5 Brawdy Plastics, Inc., produces plastic seat belt retainers for General Motors at the Brawdy Plastics plant in Buffalo, New York. After final assembly and painting, the parts are placed on a conveyor belt that moves the parts past a final inspection station. How fast the parts move past the final inspection station depends upon the line speed of the conveyor belt (feet per minute). Although faster line speeds are desirable, management is concerned that increasing the line speed too much may not provide enough time for inspectors to identify which parts are actually defective. To test this theory, Brawdy Plastics conducted an experiment in which the same batch of parts, with a known number of defective parts, was inspected using a variety of line speeds. The following data were collected....
a. Develop a scatter diagram with the line speed as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Use the least squares method to develop the estimated regression equation.
d. Predict the number of defective parts found for a line speed of 25 feet per minute.
Get solution
14.6 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 average number of passing yards per attempt (Yds/Att) and the percentage of games won (WinPct) for a random sample of 10 NFL teams for the 2011 season (NFL website, February 12, 2012)....
a. Develop a scatter diagram with the number of passing yards per attempt on the horizontal axis and the percentage of games won on the vertical axis.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Develop the estimated regression equation that could be used to predict the percentage of games won given the average number of passing yards per attempt.
d. Provide an interpretation for the slope of the estimated regression equation.
e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was 6.2. Use the estimated regression equation developed in part (c) to predict the percentage of games won by the Kansas City Chiefs. (Note: For the 2011 season the Kansas City Chiefs’ record was 7 wins and 9 losses.) Compare your prediction to the actual percentage of games won by the Kansas City Chiefs.
Get solution
14.7 A sales manager collected the following data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons....
a. Develop a scatter diagram for these data with years of experience as the independent variable..
b. Develop an estimated regression equation that can be used to predict annual sales given the years of experience.
c. Use the estimated regression equation to predict annual sales for a salesperson with 9 years of experience
Get solution
14.8 The American Association of Individual Investors (AAII) On-Line Discount Broker Survey polls members on their experiences with discount brokers. As part of the survey, members were asked to rate the quality of the speed of execution with their broker as well as provide an overall satisfaction rating for electronic trades. Possible responses (scores) were no opinion (0), unsatisfied (1), somewhat satisfied (2), satisfied (3), and very satisfied (4). For each broker, summary scores were computed by calculating a weighted average of the scores provided by each respondent. A portion of the survey results follows (AAII website, February 7, 2012)....
a. Develop a scatter diagram for these data with the speed of execution as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Develop the least squares estimated regression equation.
d. Provide an interpretation for the slope of the estimated regression equation.
e. Suppose Zecco.com developed new software to increase its speed of execution rating. If the new software is able to increase Zecco.com’s speed of execution rating from the current value of 2.5 to the average speed of execution rating for the other 10 brokerage firms that were surveyed, what value would you predict for the overall satisfaction rating?
Get solution
14.9 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. In 2011 Hertz had 320,000 cars in service and annual revenue of approximately $4.2 billion. The following data show the number of cars in service (1000s) and the annual revenue ($ millions) for six smaller car rental companies (Auto Rental News website, August 7, 2012)....
a. Develop a scatter diagram with the number of cars in service as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Use the least squares method to develop the estimated regression equation.
d. For every additional car placed in service, estimate how much annual revenue will change.
e. Fox Rent A Car has 11,000 cars in service. Use the estimated regression equation developed in part (c) to predict annual revenue for Fox Rent A Car.
Get solution
14.10
Get solution
14.11 To help consumers in purchasing a laptop computer, Consumer Reports calculates an overall test score for each computer tested based upon rating factors such as ergonomics, portability, performance, display, and battery life. Higher overall scores indicate better test results. The following data show the average retail price and the overall score for ten 13-inch models (Consumer Reports website, October 25, 2012)....
a. Develop a scatter diagram with price as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Use the least squares method to develop the estimated regression equation.
d. Provide an interpretation of the slope of the estimated regression equation.
e. Another laptop that Consumer Reports tested is the Acer Aspire S3-951-6646 Ultrabook; the price for this laptop was $700. Predict the overall score for this laptop using the estimated regression equation developed in part (c).
Get solution
14.12
Get solution
14.13 A large city hospital conducted a study to investigate the relationship between the number of unauthorized days that employees are absent per year and the distance (miles) between home and work for the employees. A sample of 10 employees was selected and the following data were collected....
a. Develop a scatter diagram for these data. Does a linear relationship appear reasonable? Explain.
b. Develop the least squares estimated regression equation that relates the distance to work to the number of days absent.
c. Predict the number of days absent for an employee who lives 5 miles from the hospital.
Get solution
14.14 Using a global-positioning-system (GPS)–based navigator for your car, you enter a destination and the system will plot a route, give spoken turn-by-turn directions, and show your progress along the route. Today, even budget units include features previously available only on more expensive models. Consumer Reports conducted extensive tests of GPS-based navigators and developed an overall rating based on factors such as ease of use, driver information, display, and battery life. The following data show the price and rating for a sample of 20 GPS units with a 4.3-inch screen that Consumer Reports tested (Consumer Reports website, April 17, 2012)....
a. Develop a scatter diagram with price as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Use the least squares method to develop the estimated regression equation.
d. Predict the rating for a GPS system with a 4.3-inch screen that has a price of $200.
Get solution
14.15 The data from exercise 1 follow....The estimated regression equation for these data is ....
a. Compute SSE, SST, and SSR using equations (12.8), (12.9), and (12.10).
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
c. Compute the sample correlation coefficient.
Get solution
14.16 The data from exercise 2 follow....The estimated regression equation for these data is ....
a. Compute SSE, SST, and SSR.
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
c. Compute the sample correlation coefficient.
Get solution
14.17 The data from exercise 3 follow....The estimated regression equation for these data is .... What percentage of the total sum of squares can be accounted for by the estimated regression equation? What is the value of the sample correlation coefficient?
Get solution
14.18 The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website, March 5, 2012). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ..., where x = price ($) and y = overall score....
a. Compute SST, SSR, and SSE.
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
c. What is the value of the sample correlation coefficient?
Get solution
14.19 In exercise 7 a sales manager collected the following data on x = annual sales and y = years of experience. The estimated regression equation for these data is .......
a. Compute SST, SSR, and SSE.
b. Compute the coefficient of determination r2. Comment on the goodness of fit.
c. What is the value of the sample correlation coefficient?
Get solution
14.20 Bicycling, the world’s leading cycling magazine, reviews hundreds of bicycles throughout the year. Its “Road-Race” category contains reviews of bikes used by riders primarily interested in racing. One of the most important factors in selecting a bike for racing is the weight of the bike. The following data show the weight (pounds) and price ($) for 10 racing bikes reviewed by the magazine (Bicycling website, March 8, 2012)....
a. Use the data to develop an estimated regression equation that could be used to estimate the price for a bike given the weight.
b. Compute r2. Did the estimated regression equation provide a good fit?
c. Predict the price for a bike that weighs 15 pounds.
Get solution
14.21 An important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation....
a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume.
b. What is the variable cost per unit produced?
c. Compute the coefficient of determination. What percentage of the variation in total cost can be explained by production volume?
d. The company’s production schedule shows 500 units must be produced next month. Predict the total cost for this operation.
Get solution
14.22 Refer to exercise 9, where the following data were used to investigate the relationship between the number of cars in service (1000s) and the annual revenue ($millions) for six smaller car rental companies (Auto Rental News website, August 7, 2012)....With x = cars in service (1000s) and y = annual revenue ($ millions), the estimated regression equation is .... For these data SSE = 1043.03.
a. Compute the coefficient of determination r2.
b. Did the estimated regression equation provide a good fit? Explain.
c. What is the value of the sample correlation coefficient? Does it reflect a strong or weak relationship between the number of cars in service and the annual revenue?
Get solution
14.23 The data from exercise 1 follow....
a. Compute the mean square error using equation (12.15).
b. Compute the standard error of the estimate using equation (12.16).
c. Compute the estimated standard deviation of b1 using equation (12.18).
d. Use the t test to test the following hypotheses (α = .05):...
e. Use the F test to test the hypotheses in part (d) at a .05 level of significance. Present the results in the analysis of variance table format.
Get solution
14.24 The data from exercise 2 follow....
a. Compute the mean square error using equation (12.15).
b. Compute the standard error of the estimate using equation (12.16).
c. Compute the estimated standard deviation of b1 using equation (12.18).
d. Use the t test to test the following hypotheses (α = .05):...
e. Use the F test to test the hypotheses in part (d) at a .05 level of significance. Present the results in the analysis of variance table format.
Get solution
14.25 The data from exercise 3 follow....
a. What is the value of the standard error of the estimate?
b. Test for a significant relationship by using the t test. Use α = .05.
c. Use the F test to test for a significant relationship. Use α = .05. What is your conclusion?
Get solution
14.26 In exercise 18 the data on price ($) and the overall score for six stereo headphones tested by Consumer Reports were as follows (Consumer Reports website, March 5, 2012)....
a. Does the t test indicate a significant relationship between price and the overall score? What is your conclusion? Use α = .05.
b. Test for a significant relationship using the F test. What is your conclusion? Use α = .05.
c. Show the ANOVA table for these data.
Get solution
14.27 To identify high-paying jobs for people who do not like stress, the following data were collected showing the average annual salary ($1000s) and the stress tolerance for a variety of occupations (Business Insider, November 8, 2013)....The stress tolerance for each job is rating on a scale from 0 to 100, where a lower rating indicates less stress.
a. Develop a scatter diagram for these data with average annual salary as the independent variable. What does the scatter diagram indicate about the relationship between the two variables?
b. Use these data to develop an estimated regression equation that can be used to predict stress tolerance given the average annual salary.
c. At the .05 level of significance, does there appear to be a significant statistical relationship between the two variables?
d. Would you feel comfortable in predicting the stress tolerance for a different occupation given the average annual salary for the occupation? Explain.
e. Does the relationship between average annual salary and stress tolerance for these data seem reasonable to you? Explain.
Get solution
14.28 In exercise 8, ratings data on x = the quality of the speed of execution and y = overall satisfaction with electronic trades provided the estimated regression equation ... (AAII website, February 7, 2012). At the .05 level of significance, test whether speed of execution and overall satisfaction are related. Show the ANOVA table. What is your conclusion?
Get solution
14.29 Refer to exercise 21, where data on production volume and cost were used to develop an estimated regression equation relating production volume and cost for a particular manufacturing operation. Use α = .05 to test whether the production volume is significantly related to the total cost. Show the ANOVA table. What is your conclusion?
Get solution
14.30 Refer to exercise 9, where the following data were used to investigate the relationship between the number of cars in service (1000s) and the annual revenue ($ millions) for six smaller car rental companies (Auto Rental News website, August 7, 2012)....With x = cars in service (1000s) and y = annual revenue ($ millions), the estimated regression equation is .... For these data SSE = 1043.03 and SST = 10,568. Do these results indicate a significant relationship between the number of cars in service and the annual revenue?
Get solution
14.31 In exercise 20, data on x = weight (pounds) and y = price ($) for 10 road-racing bikes provided the estimated regression equation ... (Bicycling website, March 8, 2012). For these data SSE = 7,102,922.54 and SST = 52,120,800. Use the F test to determine whether the weight for a bike and the price are related at the .05 level of significance.
Get solution
14.32 The data from exercise 1 follow....
a. Use equation (12.23) to estimate the standard deviation of ... when x = 4.
b. Use expression (12.24) to develop a 95% confidence interval for the expected value of y when x = 4.
c. Use equation (12.26) to estimate the standard deviation of an individual value of y when x = 4.
d. Use expression (12.27) to develop a 95% prediction interval for y when x = 4.
Get solution
14.33 The data from exercise 2 follow....
a. Estimate the standard deviation of ... when x = 8.
b. Develop a 95% confidence interval for the expected value of y when x = 8.
c. Estimate the standard deviation of an individual value of y when x = 8.
d. Develop a 95% prediction interval for y when x = 8.
Get solution
14.34 The data from exercise 3 follow....Develop the 95% confidence and prediction intervals when x = 12. Explain why these two intervals are different.
Get solution
14.35 The following data are the monthly salaries y and the grade point averages x for students who obtained a bachelor’s degree in business administration....The estimated regression equation for these data is ... and MSE = 21,284.
a. Develop a point estimate of the starting salary for a student with a GPA of 3.0.
b. Develop a 95% confidence interval for the mean starting salary for all students with a 3.0 GPA.
c. Develop a 95% prediction interval for Ryan Dailey, a student with a GPA of 3.0.
d. Discuss the differences in your answers to parts (b) and (c).
Get solution
14.36 In exercise 7, the data on y = annual sales ($ 1000s) for new customer accounts and x = number of years of experience for a sample of 10 salespersons provided the estimated regression equation .... For these data ..., and s = 4.6098.
a. Develop a 95% confidence interval for the mean annual sales for all salespersons with nine years of experience.
b. The company is considering hiring Tom Smart, a salesperson with nine years of experience. Develop a 95% prediction interval of annual sales for Tom Smart.
c. Discuss the differences in your answers to parts (a) and (b).
Get solution
14.37 In exercise 5, the following data on x = the number of defective parts found and y = the line speed (feet per minute) for a production process at Brawdy Plastics provided the estimated regression equation .......For these data SSE = 16. Develop a 95% confidence interval for the mean number of defective parts for a line speed of 25 feet per minute.
Get solution
14.38 Refer to exercise 21, where data on the production volume x and total cost y for a particular manufacturing operation were used to develop the estimated regression equation .......
a. The company’s production schedule shows that 500 units must be produced next month. Predict the total cost for next month.
b. Develop a 99% prediction interval for the total cost for next month.
c. If an accounting cost report at the end of next month shows that the actual production cost during the month was $6000, should managers be concerned about incurring such a high total cost for the month? Discuss.
Get solution
14.39 In exercise 12, the following data on x = average daily hotel room rate and y = amount spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated regression equation .... For these data SSE = 1541.4....
a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89.
b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89.
c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago.
Get solution
14.40 The commercial division of a real estate firm conducted a study to determine the extent of the relationship between annual gross rents ($1000s) and the selling price ($1000s) for apartment buildings. Data were collected on several properties sold, and Excel’s Regression tool was used to develop an estimated regression equation. A portion of the regression output follows....
a. How many apartment buildings were in the sample?
b. Write the estimated regression equation.
c. Use the t test to determine whether the selling price is related to annual gross rents. Use α = .05.
d. Use the F test to determine whether the selling price is related to annual gross rents. Use α = .05.
e. Predict the selling price of an apartment building with gross annual rents of $50,000.
Get solution
14.41 A portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal follows....
a. Write the estimated regression equation.
b. Use a t test to determine whether monthly maintenance expense is related to usage at the .05 level of significance.
c. Did the estimated regression equation provide a good fit? Explain.
Get solution
14.42 A regression model relating the number of salespersons at a branch office to annual sales at the office (in thousands of dollars) provided the following regression output....
a. Write the estimated regression equation.
b. Compute the F statistic and test the significance of the relationship at the .05 level of significance.
c. Compute the t statistic and test the significance of the relationship at the .05 level of significance.
d. Predict the annual sales at the Memphis branch office. This branch employs 12 salespersons.
Get solution
14.43
Get solution
14.44 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 organization dedicated to research, education, testing, and development of helmet safety standards. Snell “SA” (Sports Application) rated professional helmets are designed for auto racing and provide extreme impact resistance and high fire protection. One of the key factors in selecting a helmet is weight, since lower weight helmets tend to place less stress on the neck. The following data show the weight and price for 18 SA helmets (SoloRacer website, April 20, 2008)....
a. Develop a scatter diagram with weight as the independent variable.
b. Does there appear to be any relationship between these two variables?
c. Develop the estimated regression equation that could be used to predict the price given the weight.
d. Test for the significance of the relationship at the .05 level of significance.
e. Did the estimated regression equation provide a good fit? Explain.
Get solution
14.45 Given are data for two variables, x and y....
a. 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. Compute the standardized residuals.
e. Develop a plot of the standardized residuals against .... What conclusions can you draw from this plot?
Get solution
14.46 The following data were used in a regression study....
a. 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 satisfied?
Get solution
14.47 Data on advertising expenditures and revenue (in thousands of dollars) for the Four Seasons Restaurant follow....
a. Let x equal advertising expenditures and y equal revenue. Use the method of least squares to develop a straight line approximation of the relationship between the two variables.
b. Test whether revenue and advertising expenditures are related at a .05 level of significance.
c. Prepare a residual plot of ... versus .... Use the result from part (a) to obtain the values of ....
d. What conclusions can you draw from residual analysis? Should this model be used, or should we look for a better one?
Get solution
14.48 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 residual plot?
Get solution
14.49
Get solution
14.50 Consider the following data for two variables, x and y....
a. Develop a scatter diagram for these data. Does the scatter diagram indicate any outliers in the data? In general, what implications does this finding have for simple linear regression?
b. Compute the standardized residuals for these data. Do the data include any outliers? Explain.
Get solution
14.51 Consider the following data for two variables, x and y....
a. Develop a scatter diagram for these data. Does the scatter diagram indicate any influential observations? Explain.
b. Compute the standardized residuals for these data. Do the data include any outliers? Explain.
c. Do there appear to be any influential observations in these data? Explain.
Get solution
14.52 Charity Navigator is America’s leading independent charity evaluator. The following data show the total expenses ($), the percentage of the total budget spent on administrative expenses, the percentage spent on fundraising, and the percentage spent on program expenses for 10 supersized charities (Charity Navigator website, April 12, 2012). Administrativ expenses include overhead, administrative staff and associated costs, and organization; meetings. Fundraising expenses are what a charity spends to raise money, and program expenses are what the charity spends on the programs and services it exists to deliver. The sum of the three percentages does not add to 100% because of rounding....
a. Develop a scatter diagram with fundraising expenses (%) on the horizontal axis and program expenses (%) on the vertical axis. Looking at the data, do there appear to be any outliers and/or influential observations?
b. Develop an estimated regression equation that could be used to predict program expenses (%) given fundraising expenses (%).
c. Does the value for the slope of the estimated regression equation make sense in the context of this problem situation?
d. Use residual analysis to determine whether any outliers and/or influential observations are present. Briefly summarize your findings and conclusions.
Get solution
14.53 Many countries, especially those in Europe, have significant gold holdings. But many of these countries also have massive debts. The following data show the total value of gold holdings in billions of U.S. dollars and the debt as a percentage of the gross domestic product for nine countries (WordPress and Trading Economics websites, February 24, 2012)....
a. Develop a scatter diagram for the total value of a country’s gold holdings ($ billions) as the independent variable.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? Do there appear to be any outliers and/or influential observations? Explain.
c. Using the entire data set, develop the estimated regression equation that can be used to predict the debt of a country given the total value of its gold holdings.
d. Suppose that after looking at the scatter diagram in part (a) that you were able to visually identify what appears to be an influential observation. Drop this observation from the data set and fit an estimated regression equation to the remaining data. Compare the estimated slope for the new estimated regression equation to the estimated slope obtained in part (c). Does this approach confirm the conclusion you reached in part (d)? Explain.
Get solution
14.54 The following data show the annual revenue ($ millions) and the estimated team value ($ millions) for the 30 Major League Baseball teams (Forbes website, January 16, 2014).......
a. Develop a scatter diagram with Revenue on the horizontal axis and Value on the vertical axis. Looking at the scatter diagram, does it appear that there are any outliers and/ or influential observations in the data?
b. Develop the estimated regression equation that can be used to predict team value given the annual revenue.
c. Use residual analysis to determine whether any outliers and/or influential observations are present. Briefly summarize your findings and conclusions.
Get solution
14.55 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 say the S&P 500 is a better measure of stock market performance because it is broader based. The closing price for the DJIA and the S&P 500 for 15 weeks, beginning with January 6, 2012, follow (Barron’s website, April 17, 2012)....
a. Develop a scatter diagram with DJIA as the independent variable.
b. Develop the estimated regression equation.
c. Test for a significant relationship. Use α = .05.
d. Did the estimated regression equation provide a good fit? Explain.
e. Suppose that the closing price for the DJIA is 13,500. Predict the closing price for the S&P 500.
f. Should we be concerned that the DJIA value of 13,500 used to predict the S&P 500 value in part (e) is beyond the range of the data used to develop the estimated regression equation?
Get solution
14.56
Get solution
14.57
Get solution
14.58 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 usage (hours) and annual maintenance expense (in hundreds of dollars)....
a. Develop the estimated regression equation that relates annual maintenance expense to weekly usage.
b. Test the significance of the relationship in part (a) at a .05 level of significance.
c. Jensen expects to use the new machine 30 hours per week. Develop a 95% prediction interval for the company’s annual maintenance expense.
d. If the maintenance contract costs $3000 per year, would you recommend purchasing it? Why or why not?
Get solution
14.59 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....
a. Develop the least squares estimated regression equation.
b. Test to see whether the two variables are significantly related with α = .05.
c. Did the least squares line provide a good fit to the observed data? Explain.
d. Develop a 95% prediction interval for the maintenance cost for a specific bus that is 4 years old.
Get solution
14.60
Get solution
14.61 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 2007 model year Camry, the following data show the mileage and sale price for 19 sales (PriceHub website, February 24, 2012)....
a. Develop a scatter diagram with the car mileage on the horizontal axis and the price on the vertical axis.
b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables?
c. Develop the estimated regression equation that could be used to predict the price ($1000s) given the miles (1000s).
d. Test for a significant relationship at the .05 level of significance.
e. Did the estimated regression equation provide a good fit? Explain.
f. Provide an interpretation for the slope of the estimated regression equation.
g. Suppose that you are considering purchasing a previously owned 2007 Camry that has been driven 60,000 miles. Using the estimated regression equation developed in part (c), predict the price for this car. Is this the price you would offer the seller?
Get solution
