Supply the answers to the incorrect answers. Please write the question # and the question part (ex. 1a, 1b, 2a, 2b, etc...).

1.

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). Click on the datafile logo to reference the data. DATA file Date DJIA S&P January 6 12,360 1,278 January 13 12,422 1,289 January 20 12,720 1,315 January 27 12,660 1,316 February 3 12,862 1,345 February 10 12,801 1,343 February 17 12,950 1,362 February 24 12,983 1,366 March 2 12,978 1,370 March 9 12,922 1,371 March 16 13,233 1,404 March 23 13,081 1,397 March 30 13,212 1,408 April 5 13,060 1,398 April 13 12,850 1,370\fScatter diagram #1 v 9 b. Develop the estimated regression equation (to 3 decimals). Enter negative values as negative numbers. 1;: 0+ ODJIA c. Test for a significant relationship. Use a = 0.05. The pvalue is less than or equal to v w (1. Conclusion: significant relationship v w d. Did the estimated regression equation provide a good fit? 9 e. Suppose that the closing price for the DJIA is 13,500. Predict the closing price for the S&P 500 (to nearest whole number). 0 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? No vw \fGiven are five observations for two variables, :17 and 3/. Ti 4 14 7 19 16 Hi 58 48 58 12 19 a. Choose the correct scatter diagram for these data: A.- - a Y. y 60' 60 . I I II 50 so . I I 40 40 30 30 20 . 20 . ' I I 10 10 y Y. 60 60 I I . I I 50 50 I . I 40 40* 30 30* 20 . 20 . I ' I 10 10 .....|...g...q.......l...|.. .....|...|...|..... l l 10 20 30 40 50 60 X - 10 20 30 4O 50 60 b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? There appears to be a w linear relationship between :L' and y. c. Try to approximate the relationship between :0 and y by drawing a straight line through the data. Many different straight lines can be drawn v w to provide a linear approximation of the relationship between :1: and y. d. Develop the estimated regression equation by computing the values of be and In using equations: (Enter negative values as negative figure) Em 5X11:- 5) b1 2 ' 2 (M 5f b0 2 3 b1? 3) = 0 + 0 a: (to 2 decimals) e. Use the estimated regression equation to predict the value of y when a: = 5. 0 (to 2 decimals) .1) Given are five observations collected in a regression study on two variables. 2 6 9 13 20 y 7 18 9 26 23 a. Which of the following scatter diagrams accurately represents the data? A. B. 24- 24- 20- 20- 16 16 12 12- 8- 8- 4- 4 8 12 16 20 24 28 x -4 8 12 16 20 24 28 XC. - D. . 3'- y. I . 1 24 24' . . . 20 20' . . . 16 16 12; 12; I . 1 8 8' . g - I 4 4' -d ' 4 8 12 16 2O 24 28 x -4 ' 4 .4 -4' b. Develop the estimated regression equation for these data (to 1 decimal). b1: 0 b0: (3 Q 0+ 0:1: c. Use the estimated regression equation to predict the value of y when a: = 6 (to 1 decimal). 0 1? 12 16 2O 24 i 28x 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. %Working '67 45 73 55 62 % Management 22 66 48 34 a. From the following select the appropriate scatter diagram for these data with the percentage of women working in the company as the independent variable. Scatter diagram a %Management -60 ~50 ~40 -30 -20 10 20 30 40 so 60 %Working \fScatter diagram c v M b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? Positive linear relationship V w c. Try to approximate the relationship between the percentage of the women working in the company and the percetage of the management jobs held by women in that company. Many different straight lines can be drawn to provide a M approximation of the relationship between :13 and y. d. Develop the estimated regression equation by computing the values b0 and In. Enter negative values as negative numbers. Do not round intermediate calculations. Round your answers to one decimal place. 3): 0+ 0:1,- e. Predict the percentage of management jobs held by women in a company that has 60% women employees. Do not round intermediate calculations. Round your answers to nearest whole value. 0% If required, enter negative values as negative numbers. a. Select a scatter diagram with the line speed as the independent variable. Number of Defective Parts 25 20+ 15 10+ -10 -5 5 10 15 20 25 30 35 40 45 50 55 5+ Line Speed (feet per minute) -101 B. Number of Defective Parts 25 20+ 15 10 5+ -10 -5 5 10 15 20 25 30 35 40 45 50 55 -5 Line Speed (feet per minute) -10 1C. Number of Defective Parts 25+ 20+ 15- 5- 10 -5 5 10 15 20 25 30 35 40 45 50 55 -5+ Line Speed (feet per minute) -101 D. Number of Defective Parts 25I 20 15- 10 5 -10 -5 5 10 15 20 25 30 35 40 45 50 55 -5 Line Speed (feet per minute) -10 1k'9 b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? Negative relationship v M c. Use the least squares method to develop the estimated regression equation (to 1 decimal). 2 0+ 0:1: . Predict the number of defective parts found for a line speed of 25 feet per minute. 0 11:2) \fThe 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). Team Yds /Att WinPct Arizona Cardinals 7.2 51 Atlanta Falcons 6.4 36 Carolina Panthers 7.9 60 Chicago Bears 7.4 46 Dallas Cowboys 7.0 41 New England Patriots 5.4 14 Philadelphia Eagles 8.3 66 Seattle Seahawks 7.4 51 St. Louis Rams 6.9 37 Tampa Bay Buccaneers 8.4 70a. Choose the correct 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. A. WinPct B. `WinPct 80 80 70+ 70+ 60+ 60+ 50+ 50+ 40- 40+ 30+ 30+ 20+ 20+ 10+ 10+ 15 6 7 8 9 Yds/Att 6 7 18 9 Yds/AttC. WinPct D. WinPct 80+ -80+ 70+ 70+ 60+ 60+ 50+ 50+ 40+ 40+ 30+ 30+ 20+ 20+ 10+ 10+ 6 7 8 9 15 Yds/Att 6 7 9 Yds/Att Ab. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a 9 linear relationship between a: = average number of passing yards per attempt and y = the percentage of games won by the team. 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. Enter negative value as negative number. WinPct : 0 +( 0)(Yds/Att) (to 4 decimals) d. Provide an interpretation for the slope of the estimated regression equation (to 1 decimal). The slope of the estimated regression line is approximately 0. So, for every 9 of one yard in the average number of passes per attempt, the percentage of games won by the team increases by 8%. e. For the 2011 season, the average number of passing yards per attempt for the Kansas City Chiefs was was 7.3. 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.) 0 % (to 2 decimals) Compare your prediction to the actual percentage of games won by the Kansas City Chiefs. Considering the small data size, the prediction made using the estimated regression equation b0. 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. Click on the datafile logo to reference the data. DAM" Years of Annual Sales Salesperson Experience ($10005) 1 1 80 2 3 97 3 4 92 4 4 102 5 6 103 6 8 11 1 7 10 119 8 10 123 9 11 117 10 13 136 a. Choose the correct scatter diagram for these data with years of experience as the independent variable. A. 140 Annual Sales ($1000s) +120 -100 +80 +60 +40 +20 Years of Experience 4 6 8 10 12 14 B. 140 Annual Sales ($1000s) -120 +100 +80 . +60 +40 +20 Years of Experience 4 6 8 10 12 14C. 140 Annual Sales ($1000s) 120 100 +80 +60 -40 +20 Years of Experience $8 10 12 14 B b. Develop an estimated regression equation that can be used to predict annual sales given the years of experience. Compute b1 and bo (to the nearest whole number). b1 bo Complete the estimated regression equation below. y = * + c. Use the estimated regression equation to predict annual sales for a salesperson with 9 years of experience (to the nearest whole number). $ XA B C D E F G H Salesperson Years J K Sales L M 80 97 AA WI 92 CO OO VO UI A W N 102 6 103 DO JOVI AWN 8 111 10 119 10 123 10 11 117 11 10 13 136 12 13 14 15 16 17 18 19 20David's Landscaping has collected data on home values (in thousands of $) and expenditures (in thousands of $) on landscaping with the hope of developing a predictive model to help marketing to potential new clients. Data for 14 households may be found in the file Landscape. Click on the datafile logo to reference the data. DATA!\" If required, enter negative values as negative numbers. a. Select a scatter diagram with home value as the independent variable. A' Landscape Expenditures {$10001 a '20 . a ' a . a '15 . I a a a '10 . a '5 Home Value {$10001 290 490 690 890 . \fC. Landscape Expenditures 31000: a a '20 '- . I '15 g I a a I '10 . a a '5 Horne Value l$1000i 290 490 690 ago . 9 b. What does the scatter plot developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a Q0 linear relationship between the two variables. c. Use the least squares method to develop the estimated regression equation (to 5 decimals). = 02+ 0 . For every additional $1000 in home value, estimate how much additional will be spent on landscaping (to 2 decimals). $ 0 e. Use the equation estimated in part (c) to predict the landscaping expenditures for a home valued at $575,000 (to the nearest whole number). $ 0 1V2> A B C Home Value ($1000) Landscape Expenditures ($1000) 242 8.1 321 10.8 198 12.2 340 16.2 5 0 J O) OF A W N 300 15.6 400 18.9 800 23.5 200 9.5 10 521 17.5 11 547 22 12 437 12.1 13 464 14 14 635 17.9 15 356 13.9 16 17 18To help consumers in purchasing a laptop computer, Consumer Reports calculates an overall test score for each computer tested based upon rating factors such as ergonomics, portability, performance, display, and battery life. Higher overall scores indicate better test results. The following data show the average retail price and the overall score for ten 13-inch models (Consumer Reports website). Click on the datafile logo to reference the data. DATA file Price Overall Brand & Model ($ ) Score Samsung Ultrabook NP900X3C-A01US 1250 83 Apple MacBook Air MC965LL/A 1300 83 Apple MacBook Air MD231LL/A 1200 82 HP ENVY 13-2050nr Spectre XT 950 79 Sony VAIO SVS13112FXB 800 77 Acer Aspire S5-391-9880 Ultrabook 1200 74 Apple MacBook Pro MD101LL/A 1200 74 Apple MacBook Pro MD313LL/A 1000 73 Dell Inspiron I13Z-6591SLV 700 67 Samsung NP53503C-A01US 600 63a. Select the correct scatter diagram with price as the independent variable. A. Overall Score 85+ 80+ 75+ 70+ 65+ 60+ 55+ 600 800 1000 1200 1400 Price ($)\fOverall Score 85 BO 75 70 65 60 55 . . . i . . . . l . . . . l . . 1000 1200 1400 Price l$l I 800 k~0 b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? The scatter diagram indicates a @ linear relationship between the two variables. c. Use the least squares method to develop the estimated regression equation (to 4 decimals). : 0+ 053 . Provide an interpretation of the slope of the estimated regression equation (to the nearest whole number). The slope means that spending an additional $100 in price will K0 the overall score by approximately 0 points. e. Another laptop that Consumer Reports tested is the Acer Aspire 539516646 Ultrabook; the price for this laptop was $700. Predict the overall score for this a Q) laptop using the estimated regression equation developed in part (c) (to 1 decimal). (3 A B C D 1 Brand & Model Price ($) Overall Score 2 Samsung Ultrabook NP900X3C-AOIUS 1250 83 3 Apple MacBook Air MC965LL/A 1300 83 4 Apple MacBook Air MD231LL/A 1200 82 5 HP ENVY 13-2050nr Spectre XT 950 79 6 Sony VAIO SVS13112FXB 800 77 7 Acer Aspire $5-391-9880 Ultrabook 1200 74 8 Apple MacBook Pro MD10ILL/A 1200 74 9 Apple MacBook Pro MD313LL/A 1000 73 10 Dell Inspiron I13Z-6591SLV 700 67 11 Samsung NP535U3C-AOIUS 600 63 12 13 1 1A 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. Excel file: data 14-13.xlsx Distance to Work Number of Days (miles) Absent 1 8 3 5 4 8 6 7 8 6 10 3 12 5 14 2 14 4 18 2 If required, enter negative values as negative numbers. a. Select the correct scatter diagram for these data. A" Number of Days Absent 10 B I I I 6 I I I 4 I I 2 I I 2 4 6 B 10 12 14 16 18 20 Distance to Work (miles: 3' Number of Days Absent 10 8 I I I 6 I I 4 I I I 2 I I 2 4 6 B 10 12 14 16 18 20 Distance to Work (miles: C. 104 Number of Days Absent 8+ 4- 2- 2 4 6 8 10 12 14 16 18 20 Distance to Work (miles) Graph A Does a linear relationship appear reasonable? Yes, a negative one b. Develop the least squares estimated regression equation that relates the distance to work to the number of days absent (to 4 decimals). y = + c. Predict the number of days absent for an employee that lives 5 miles from the hospital (to nearest whole number). days\fThe 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). Click on the datafile logo to reference the data. DATA file Date DJIA S&P January 6 12,360 1,278 January 13 12,422 1,289 January 20 12,720 1,315 January 27 12,660 1,316 February 3 12,862 1,345 February 10 12,801 1,343 February 17 12,950 1,362 February 24 12,983 1,366 March 2 12,978 1,370 March 9 12,922 1,371 March 16 13,233 1,404 March 23 13,081 1,397 March 30 13,212 1,408 April 5 13,060 1,398 April 13 12,850 1,370\f2. S&P 500 1400 1380 1360 1340 1320 1300 1280 1260 DJIA 12200 12400 12600 12800 13000 13200\fScatter diagram #1 v M b. Develop the estimated regression equation (to 3 decimals). Enter negative values as negative numbers. ,3: 0+ oDJIA c. Test for a significant relationship. Use a = 0.05. The pvalue is less than or equal to v Q9 (1. Conclusion: significant relationship v Q0 d. Did the estimated regression equation provide a good fit? w e. Suppose that the closing price for the DJIA is 13,500. Predict the closing price for the S&P 500 (to nearest whole number). 0 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? No vw