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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
15. Speed of Overnight Delivery Services. A test was conducted for two overnight mail delivery services. Two samples of identical deliveries were set up so that both delivery services were notified of the need for a delivery at the same time. The hours required to make each delivery follow. Do the
14. On-Time Arrivals at Busy Airports. Percents of on-time arrivals for flights in the past two years were collected for 11 randomly selected airports. Data for these airports follow. Use a = .05 to test the hypothesis that there is no difference between the median percent of on-time arrivals for
13. Time Needed to Fall Asleep. A sample of 10 men was used in a study to test the effects of a relaxant on the time required to fall asleep. Data for 10 subjects showing the number of minutes required to fall asleep with and without the relaxant follow. Use a .05 level of significance to determine
12. Comparing Fuel Additives. Two fuel additives are tested to determine their effect on kilometers per liter for passenger cars. Test results for 12 cars follow; each car was tested with both fuel additives. Use a = .05 and the Wilcoxon signed-rank test to see whether there is a significant
11. Share of Personal Computer Market. Competition in the personal computer market is intense. A sample of 450 purchases showed 202 Brand A computers, 175 Brand B computers, and 73 other computers. Use a .05 level of significance to test the null hypothesis that Brand A and Brand B have the same
10. Favorite Prime-Time Network Series. Nielsen Media Research identified The Big Bang Theory and This is Us as the two top-rated prime-time television series. In a local television preference survey, 750 individuals were asked to indicate their favorite prime-time television series: Three hundred
9. Economic Conditions and Children’s Futures. In a recent poll, six hundred adults were asked a series of questions about the state of the economy and their children’s future. One question was, “Do you expect your children to have a better life than you have had, a worse life, or a life
8. Ideal Pace of Life. A Pew Research Center survey asked adults if their ideal place to live would have a faster pace of life or a slower pace of life. A preliminary sample of 16 respondents showed 4 preferred a faster pace of life, 11 preferred a slower pace of life, and 1 said it did not
7. Profitability of Stock Splits. Are stock splits beneficial to stockholders? SNL Financial studied stock splits in the banking industry over an 18-month period. For a sample of 20 stock splits, 14 led to an increase in investment value, 4 led to a decrease in investment value, and 2 resulted in
6. Median Annual Income in Chicago. The median annual income for families living in the United States is $56,200. Annual incomes in thousands of dollars for a sample of 50 families living in Chicago, Illinois, are shown. Use the sample data to see if it can be concluded that the families living in
5. Median Price of Homes in Austin. In 2015 the median price of homes in Austin, Texas, was $248,640 (AustinHomeSearch website). A sample of 200 homes sold in the south Austin suburb of Westlake Hills found 111 homes with sales prices over $248,640 and 89 homes with sales prices under $248,640. Can
4. Assets of Stock Mutual Funds. Net assets for the 50 largest stock mutual funds show a median of $15 billion. A sample of 10 of the 50 largest bond mutual funds follows.Bond Fund Net Assets Bond Fund Net Assets Fidelity Intl Bond 6.1 T Rowe Price New Income 6.9 Franklin CA TF 11.7 Vanguard GNMA
3. Employees at Fast-Food Restaurants. The median number of part-time employees at fast-food restaurants in a particular city was known to be 18 last year. City officials think the use of part-time employees may be increasing. A sample of nine fast-food restaurants showed that seven restaurants
2. Ten individuals participated in a taste test involving two brands of a product. Sample results show 7 preferred brand A, 2 preferred brand B, and 1 was unable to state a preference. With a = .05, test for a significant difference in the preferences for the two brands. What is your conclusion?
1. The following hypothesis test is to be conducted.H0: Median ≤ 150 Ha: Median > 150 A sample of 30 provided 22 observations greater than 150, 3 observations equal to 150, and 5 observations less than 150. Use a = .01. What is your conclusion?
55. Deseasonalizing Boat Trailer Sales Data. Refer to the Hudson Marine data in exercise 53.a. Deseasonalize the data and use the deseasonalized time series to identify the trend.b. Use the results of part (a) to develop a quarterly forecast for next year based on trend.c. Use the seasonal indexes
54. Estimating Seasonal Effects in Boat Trailer Sales. Refer to the Hudson Marine problem in exercise 53.a. Compute the centered moving average values for this time series.b. Construct a time series plot that also shows the centered moving average and original time series on the same graph. Discuss
53. Boat Trailer Sales with Seasonality. Refer to the Hudson Marine problem in exercise 52. Suppose the quarterly sales values for the seven years of historical data are as follows.Total Yearly Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 Sales 1 6 15 10 4 35 2 10 18 15 7 50 3 14 26 23 12 75 4 19
52. Boat Trailer Sales. Hudson Marine provides boat sales, service, and maintenance.Boat trailers are one of its top sales items. The following table reports the number of trailers sold for the last seven years.Year 1 2 3 4 5 6 7 Number Sold 35 50 75 90 105 110 130a. Construct a time series plot.
51. Sales of Musical Instruments Using Trend and Seasonality. Refer to the Costello Music Company time series in exercise 49.a. Deseasonalize the data and use the deseasonalized time series to identify the trend.b. Use the results of part (a) to develop a quarterly forecast for next year based on
50. Musical Instrument Sales with Decomposition. Refer to the Costello Music Company problem in exercise 49.a. Using time series decomposition, compute the seasonal indexes for the four quarters.b. When does Costello Music experience the largest seasonal effect? Does this result appear reasonable?
49. Musical Instrument Sales with Seasonality. Consider the Costello Music Company problem in exercise 48. The quarterly sales data follow.Total Yearly Year Quarter 1 Quarter 2 Quarter 3 Quarter 4 Sales 1 4 2 1 5 12 2 6 4 4 14 28 3 10 3 5 16 34 4 12 9 7 22 50 5 18 10 13 35 76 PianoSalesa. Use the
48. Musical Instrument Sales. The Costello Music Company has been in business for five years. During that time, sales of pianos increased from 12 units in the first year to 76 units in the most recent year. Fred Costello, the firm’s owner, wants to develop a forecast of piano sales for the coming
47. Disney Price of Admission. The following data show the price in dollars for a general admission ticket to the Magic Kingdom at Disney World from the year 2000 (period 1)to 2017 (period 18) (Travel 1 Leisure website). These data are in the file DisneyPrices.Year Period Price of Admission ($)2000
46. Lost Sales. The Mayfair Department Store in Davenport, Iowa, is trying to determine the amount of sales lost while it was shut down during July and August because of damage caused by the Mississippi River flood. Sales data for January through June follow.Month Sales ($1000s) Month Sales
45. Store Revenue. Annual retail store revenue for Apple from 2007 to 2017 are shown below (investorapple website).Year Period Retail Store Revenue ($ billions)2007 1 $4.115 2008 2 $6.310 2009 3 $6.577 2010 4 $9.080 2011 5 $14.127 2012 6 $18.828 2013 7 $20.228 2014 8 $21.462 2015 9 $28.109 2016 10
44. Crude Oil Cost. The data contained in the file CrudeCost shows the U.S. refiner acquisition cost of crude oil in dollars per barrel (Energy Information Administration website).a. Construct a time series plot. What type of pattern exists in the data?b. Compute the linear trend equation for the
43. Demand for Dairy Products. United Dairies, Inc., supplies milk to several independent grocers throughout Dade County, Florida. Managers at United Dairies want to develop a forecast of the number of 1.9 liter containers of milk sold per week. Sales data for the past 12 weeks follow.Week Sales
42. Portfolio Composition. The following table reports the percentage of stocks in a portfolio for nine quarters.Quarter Stock %1st—Year 1 29.8 2nd—Year 1 31.0 3rd—Year 1 29.9 4th—Year 1 30.1 1st—Year 2 32.2 2nd—Year 2 31.5 3rd—Year 2 32.0 4th—Year 2 31.9 1st—Year 3 30.0a.
41. Demand for Consumer Goods. The weekly demand (in cases) for a particular brand of automatic dishwasher detergent for a chain of grocery stores located in Columbus, Ohio, follows.Week Demand Week Demand 1 22 6 24 2 18 7 20 3 23 8 19 4 21 9 18 5 17 10 21a. Construct a time series plot. What type
40. Electricity Consumption Using Deseasonalization. Electric power consumption is measured in kilowatt-hours (kWh). The local utility company offers an interrupt program whereby commercial customers that participate receive favorable rates but must agree to cut back consumption if the utility
39. Air Pollution Using Deseasonalization. Air pollution control specialists in southern California monitor the amount of ozone, carbon dioxide, and nitrogen dioxide in the air on an hourly basis. The hourly time series data exhibit seasonality, with the levels of pollutants showing patterns over
38. Lawn Maintenance Expenses Using Deseasonalization. Three years of monthly lawn-maintenance expenses ($) for a six-unit apartment house in southern Florida follow.Month Year 1 Year 2 Year 3 January 170 180 195 February 180 205 210 March 205 215 230 April 230 245 280 May 240 265 290 June 315 330
37. Text Book Sales Using Deseasonalization. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow.Quarter Year 1 Year 2 Year 3 1 1690 1800 1850 2 940 900 1100 3 2625 2900 2930 4 2500 2360 2615a. Construct a time series plot. What type of pattern
36. Refer to exercise 35.a. Deseasonalize the time series using the adjusted seasonal indexes computed in part (c) of exercise 35.b. Using statistical software, compute the linear trend regression equation for the deseasonalized data.c. Compute the deseasonalized quarterly trend forecast for year
35. Consider the following time series data.Quarter Year 1 Year 2 Year 3 1 4 6 7 2 2 3 6 3 3 5 6 4 5 7 8a. Construct a time series plot. What type of pattern exists in the data?b. Show the four-quarter and centered moving average values for this time series.c. Compute seasonal indexes and adjusted
34. Lawn Maintenance. Three years of monthly lawn-maintenance expenses ($) for a six-unit apartment house in southern Florida follow.Month Year 1 Year 2 Year 3 January 170 180 195 February 180 205 210 March 205 215 230 April 230 245 280 May 240 265 290 June 315 330 390 July 360 400 420 August 290
33. Power Consumption. Electric power consumption is measured in kilowatt-hours(kWh). The local utility company offers an interrupt program whereby commercial customers that participate receive favorable rates but must agree to cut back consumption if the utility requests them to do so. Timko
32. Seasonal Sales. South Shore Construction builds permanent docks and seawalls along the southern shore of Long Island, New York. Although the firm has been in business only five years, revenue has increased from $308,000 in the first year of operation to$1,084,000 in the most recent year. The
31. Air Pollution. Air pollution control specialists in southern California monitor the amount of ozone, carbon dioxide, and nitrogen dioxide in the air on an hourly basis.The hourly time series data exhibit seasonality, with the levels of pollutants showing patterns that vary over the hours in the
30. Textbook Sales. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow.Quarter Year 1 Year 2 Year 3 1 1690 1800 1850 2 940 900 1100 3 2625 2900 2930 4 2500 2360 2615b. Use the following dummy variables to develop an estimated regression equation
29. Consider the following time series data.Quarter Year 1 Year 2 Year 3 1 4 6 7 2 2 3 6 3 3 5 6 4 5 7 8a. Construct a time series plot. What type of pattern exists in the data?b. Use the following dummy variables to develop an estimated regression equation to account for any seasonal and linear
28. Consider the following time series.Quarter Year 1 Year 2 Year 3 1 71 68 62 2 49 41 51 3 58 60 53 4 78 81 72a. Construct a time series plot. What type of pattern exists in the data?b. Use the following dummy variables to develop an estimated regression equation to account for seasonal effects in
27. Google Revenue. The following data show Google revenue from 2008 (period 1) to 2017 (period 10) in billions of dollars (Alphabet, Inc. annual reports). These data are in the file GoogleRevenue.Year Period Annual Revenue ($ Billions)2008 1 $21.80 2009 2 $23.65 2010 3 $29.32 2011 4 $37.91 2012 5
26. Forecasting Revenue. Giovanni Food Products produces and sells frozen pizzas to public schools throughout the eastern United States. Using a very aggressive marketing strategy they have been able to increase their annual revenue by approximately$10 million over the past 10 years. But increased
25. Netflix Subscribers. The following data show the number of Netflix subscribers worldwide for the years 2012 (period 1) to 2017 (period 6) (datawrapper website). The data are in the file NetflixSubscribers.Year Period Subscribers (Millions)2012 1 33.27 2013 2 44.35 2014 3 57.39 2015 4 74.76 2016
24. Mortgage Interest Rates. The following data shows the average interest rate (%) for a 30-year fixed-rate mortgage over a ten-year period (FreddieMac website).Period Interest Rate (%)1 6.41 2 6.34 3 6.03 4 5.04 5 4.69 6 4.45 7 3.66 8 3.98 9 4.17 10 3.85a. Construct a time series plot. Do you
23. Performance Footwear Sales. Skechers is a performance footwear company headquartered in Manhattan Beach, California. The sales for Skechers (in billions of dollars) for 2012 (period 1) to 2017 (period 6) are in the file SkechersSales (annualreports.com).a. Construct a time-series plot. What
22. Administrative Expenses. The Seneca Children’s Fund (SCF) is a local charity that runs a summer camp for disadvantaged children. The fund’s board of directors has been working very hard in recent years to decrease the amount of overhead expenses, a major factor in how charities are rated by
21. Kentucky State Revenue. The general fund revenue receipts for the state of Kentucky for 2003 (period 1) to 2017 (period 15) are in the file KYRevenue (ky.gov website).a. Construct a time-series plot. What type of pattern exists in the data?b. Develop a linear trend equation for this time
20. Consider the following time series.t 1 2 3 4 5 6 7 Yt 82 60 44 35 30 29 35a. Construct a time series plot. What type of pattern exists in the data?b. Using statistical software, develop the quadratic trend equation for the time series.c. What is the forecast for t = 8?
19. Consider the following time series.t 1 2 3 4 5 6 7 Yt 120 110 100 96 94 92 88a. Construct a time series plot. What type of pattern exists in the data?b. Develop the linear trend equation for this time series.c. What is the forecast for t = 8?
18. Consider the following time series data.t 1 2 3 4 5 6 7 yt 10 9 7 8 6 4 4a. Construct a time series plot. What type of pattern exists in the data?b. Develop the linear trend equation for this time series.c. What is the forecast for t = 8?
17. Consider the following time series data.t 1 2 3 4 5 Yt 6 11 9 14 15a. Construct a time series plot. What type of pattern exists in the data?b. Develop the linear trend equation for this time series.c. What is the forecast for t = 6?
16. Home Prices. The U.S. Census Bureau tracks the median price for new home sales by month of year. The median prices for April for 22 years follow (U.S. Census Bureau website).Year Price ($1000s) Year Price ($1000s)1 130.0 12 175.2 2 121.0 13 187.1 3 120.0 14 189.5 4 127.0 15 222.3 5 129.0 16
15. Commodity Futures Index. Ten weeks of data on the Commodity Futures Index are 7.35, 7.40, 7.55, 7.56, 7.60, 7.52, 7.52, 7.70, 7.62, and 7.55.a. Construct a time series plot. What type of pattern exists in the data?b. Compute the exponential smoothing forecasts for a = .2.c. Compute the
14. Sales Forecasts. The following time series shows the sales of a particular product over the past 12 months.Month Sales Month Sales 1 105 7 145 2 135 8 140 3 120 9 100 4 105 10 80 5 90 11 100 6 120 12 110a. Construct a time series plot. What type of pattern exists in the data?b. Use a = .3 to
13. Building Contracts. The values of Alabama building contracts (in $ millions) for a 12-month period follow.240 350 230 260 280 320 220 310 240 310 240 230a. Construct a time series plot. What type of pattern exists in the data?b. Compare the three-month moving average approach with the
12. Bond Interest Rates. Corporate triple-A bond interest rates for 12 consecutive months follow.9.5 9.3 9.4 9.6 9.8 9.7 9.8 10.5 9.9 9.7 9.6 9.6a. Construct a time series plot. What type of pattern exists in the data?b. Develop three-month and four-month moving averages for this time series. Does
11. On-Time Shipments. For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83.a. Construct a time series plot. What type of pattern exists in the data?b. Compare the three-month moving average
10. With a smoothing constant of a = .2, equation (17.2) shows that the forecast for week 13 of the gasoline sales data from Table 17.1 is given by F13 = .2Y12 + .8F12.However, the forecast for week 12 is given by F12 = .2Y11 + .8F11. Thus, we could combine these two results to show that the
9. With the gasoline time series data from Table 17.1, show the exponential smoothing forecasts using a = .1.a. Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of a = .1 or a = .2 for the gasoline sales time series?b. Are the results the same if you apply MAE as
8. Refer again to the gasoline sales time series data in Table 17.1.a. Using a weight of 1/2 for the most recent observation, 1/3 for the second most recent observation, and 1/6 for third most recent observation, compute a three-week weighted moving average for the time series.b. Compute the MSE
7. Refer to the gasoline sales time series data in Table 17.1.a. Compute four-week and five-week moving averages for the time series.b. Compute the MSE for the four-week and five-week moving average forecasts.c. What appears to be the best number of weeks of past data (three, four, or five)to use
6. Consider the following time series data.Month 1 2 3 4 5 6 7 Value 24 13 20 12 19 23 15 Construct a time series plot. What type of pattern exists in the data?a. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 8.b. Use a = .2 to compute the
5. Consider the following time series data.Week 1 2 3 4 5 6 Value 18 13 16 11 17 14a. Construct a time series plot. What type of pattern exists in the data?b. Develop the three-week moving average forecasts for this time series. Compute MSE and a forecast for week 7.c. Use a = .2 to compute the
4. Consider the following time series data.Month 1 2 3 4 5 6 7 Value 24 13 20 12 19 23 15a. Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8?b. Compute MSE using the average of all the data available as the forecast for the next period.
3. Exercises 1 and 2 used different forecasting methods. Which method appears to provide the more accurate forecasts for the historical data? Explain.
2. Refer to the time series data in exercise 1. Using the average of all the historical data as a forecast for the next period, compute the following measures of forecast accuracy.a. Mean absolute error.b. Mean squared error.c. Mean absolute percentage error.d. What is the forecast for week 7?
1. Consider the following time series data.Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.a. Mean absolute error.b. Mean squared error.c. Mean absolute percentage error.d.
36. Shopper Comfort and Level of Browsing Activity. A study was conducted to investigate browsing activity by shoppers. Shoppers were classified as nonbrowsers, light browsers, and heavy browsers. For each shopper in the study, a measure was obtained to determine how comfortable the shopper was in
35. Estimating Fuel Mileage by Car Size. The U.S. Department of Energy’s Fuel Economy Guide provides fuel efficiency data for cars and trucks(www.fueleconomy.gov). The file FuelEconomy2019 provides a portion of the data for 387 vehicles from the 2019 model year. The column labeled Class
34. Autocorrelation in Audit Delay Multiple Regression. Refer to the data in exercise 31.a. Develop an estimated regression equation that can be used to predict Delay by using Industry and Quality.b. Plot the residuals obtained from the estimated regression equation developed in part (a) as a
33. Autocorrelation in Audit Delay Simple Regression. Refer to the data in exercise 31. Consider a model in which only Industry is used to predict Delay. At a .01 level of significance, test for any positive autocorrelation in the data.
32. Delays in Company Audits. A study investigated the relationship between audit delay (Delay), the length of time from a company’s fiscal year-end to the date of the auditor’s report, and variables that describe the client and the auditor. Some of the independent variables that were included
31. Predicting ERA in Major League Baseball. In baseball, an earned run is any run the opposing team scores off a pitcher except for a run scored as a result of fielding errors.The earned run average (ERA) is a statistic commonly used to compare the performance of pitchers; the ERA of a pitcher is
30. Bike Prices. Consumer Reports tested 19 different brands and models of road, fitness, and comfort bikes. Road bikes are designed for long road trips; fitness bikes are designed for regular workouts or daily commutes; and comfort bikes are designed for leisure rides on typically flat roads. The
29. Years to Maturity and Bond Yield. A sample containing years to maturity and yield (%)CorporateBonds for 40 corporate bonds is contained in the filea. Develop a scatter diagram of the data using x = years to maturity as the independent variable. Does a simple linear regression model appear to be
28. Autocorrelation in Sales Data. Refer to the Cravens data set in Table 16.5. In Section 16.3 we showed that the estimated regression equation involving Accounts, AdvExp, Poten, and Share had an adjusted coefficient of determination of 88.1%. Use the .05 level of significance and apply the
27. Autocorrelation in Stock Price. The following data show the daily closing prices (in dollars per share) for a stock.Date Price ($)Nov. 3 82.87 Nov. 4 83.00 Nov. 7 83.61 Nov. 8 83.15 Nov. 9 82.84 Nov. 10 83.99 Nov. 11 84.55 Nov. 14 84.36 Nov. 15 85.53 Nov. 16 86.54 Nov. 17 86.89 Nov. 18 87.77
26. Effect of Banner Ad Size and Design. Mbuy is a media consulting firm that provides advice to companies on how to allocate their advertising budgets. Mbuy designed a factorial experiment to test the effect of the size of a banner ad on a website and the ad design on the number (in thousands) of
25. Car Tune-Up Times. An automobile dealer conducted a test to determine whether the time needed to complete a minor engine tune-up depends on whether a computerized engine analyzer or an electronic analyzer is used. Because tune-up time varies among compact, intermediate, and full-sized cars, the
24. Estimating Drying Time of Different Paints. Four different paints are advertised as having the same drying time. To check the manufacturers’ claims, five samples were tested for each of the paints. The time in minutes until the paint was dry enough for a second coat to be applied was recorded
23. Estimating Process Time on Different Machines. The Jacobs Chemical Company wants to estimate the mean time (minutes) required to process a batch of material on mixer machines produced by three different manufacturers. To limit the cost of testing, four batches of material were mixed on machines
22. Write a multiple regression equation that can be used to analyze the data for a two-factorial design with two levels for factor A and three levels for factor B. Define all variables.
21. Write a multiple regression equation that can be used to analyze the data for a randomized block design involving three treatments and two blocks. Define all variables.
20. Consider a completely randomized design involving four treatments: A, B, C, and D.Write a multiple regression equation that can be used to analyze these data. Define all variables.
19. Predicting Risk of Stroke with Interaction Effects. Refer to exercise 14. Using age, blood pressure, whether a person is a smoker, and any interaction involving those variables, develop an estimated regression equation that can be used to predict risk. Briefly describe the process you used to
18. Predicting Sagarin’s RPG Baseball Statistic. Jeff Sagarin has been providing sports ratings for USA Today since 1985. In baseball his predicted RPG (runs per game)statistic takes into account the entire player’s offensive statistics, and is claimed to be the best measure of a player’s
17. Predicting LPGA Player Average Score with an Interaction Effect. 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 LPGA2014Stats (LPGA
16. Duration of Unemployment. A study provided data on variables that may be related to the number of weeks a person has been jobless. The dependent variable in the study(Weeks) was defined as the number of weeks a person has been jobless due to a layoff.The following independent variables were
15. Natural Gas Utility Bills. In 2016, the average monthly residential natural gas bill for Black Hills Energy customers in Cheyenne, Wyoming, is $67.95 (Wyoming Public Service Commission website). How is the monthly average gas bill for a Cheyenne home related to the square meter area, number of
14. Predicting the Risk of 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. Data from a portion of this study follow. Risk is interpreted as the probability(times 100) that a person will have a
13. Predicting LPGA Player’s Total Earnings. Refer to the description in exercise 12.a. Develop an estimated regression equation that can be used to predict the total earnings for all events given the average number of putts taken on greens hit in regulation.b. Develop an estimated regression
12. Predicting LPGA Player’s Average Score. 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 LPGA2014Stats (LPGA website). Earnings ($1000s)
11. In a regression analysis involving 30 observations, the following estimated regression equation was obtained:yˆ 5 17.6 1 3.8x1 2 2.3x2 1 7.6x3 1 2.7x4 For this estimated regression equation SST = 1805 and SSR = 1760.a. At a = .05, test the significance of the relationship among the
10. In a regression analysis involving 27 observations, the following estimated regression equation was developed:yˆ 5 25.2 1 5.5x1 For this estimated regression equation SST = 1550 and SSE = 520.a. At a = .05, test whether x1 is significant.Suppose that variables x2 and x3 are added to the model
9. Movie Ratings. As of September 4, 2016, the film Suicide Squad had an average rating of 3.7 out of 5 based on 117,323 viewer ratings (Rotten Tomatoes website). How are the viewer ratings of Suicide Squad related to the viewer age and the viewer ratings of The Secret Life of Pets? The file
8. Classic Car Rating and Price. Corvette, Ferrari, and Jaguar produced a variety of classic cars that continue to increase in value. The following data, based upon the Martin Rating System for Collectible Cars, show the rarity rating (1–20) and the high price ($1000) for 15 classic cars.Year
7. Washing Machine Capacity and Price. Home Depot, a home-improvement retailer, sells several brands of washing machines. The following table contains a sample of 24 models of full-size washing machines sold by Home Depot in 2016, with each observation recording the washing machine capacity (in
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