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Q: The dataset posted below lists a sample of months and the advertising budget (in hundreds of dollars) for TV, radio and newspaper advertisements. Also included is whether a coupon was published for that month and the resulting sales (in thousands of dollars). a) Develop a multiple regression model predicting the sales based off the four predictor variables: TV, radio, and newspaper advertising budget and whether a coupon is used.   Recode Coupon as 0 = No and 1 = Yes.   Report the estimated regression equation (Solve in Excel) TV ($100) radio ($100) newspaper ($100) Coupon sales ($1000) 0.7 39.6 8.7 No 1.6   230.1 37.8 69.2 No 22.1   4.1 11.6 5.7 Yes 3.2   44.5 39.3 45.1 No 10.4   250.9 36.5 72.3 No 22.2   8.6 2.1 1 No 4.8   17.2 45.9 69.3 Yes 9.3   104.6 5.7 34.4 No 10.4   216.8 43.9 27.2 Yes 22.3   5.4 29.9 9.4 No 5.3   69 9.3 0.9 No 9.3   70.6 16 40.8 No 10.5   151.5 41.3 58.5 No 18.5   195.4 47.7 52.9 Yes 22.4   13.1 0.4 25.6 Yes 5.3   76.4 0.8 14.8 No 9.4   156.6 2.6 8.3 No 10.5   180.8 10.8 58.4 No 12.9   248.8 27.1 22.9 No 18.9   216.4 41.7 39.6 Yes 22.6   7.3 28.1 41.4 Yes 5.5   8.7 48.9 75 No 7.2   95.7 1.4 7.4 No 9.5   199.8 2.6 21.2 Yes 10.6   206.9 8.4 26.4 No 12.9   237.4 27.5 11 No 18.9   205 45.1 19.6 Yes 22.6   13.2 15.9 49.6 No 5.6   25 11 29.7 No 7.2   31.5 24.6 2.2 No 9.5   89.7 9.9 35.7 Yes 10.6   57.5 32.8 23.5 No 11.8   88.3 25.5 73.4 No 12.9   204.1 32.9 46 Yes 19   239.9 41.5 18.5 Yes 23.2   8.4 27.2 2.1 No 5.7   28.6 1.5 33 No 7.3   25.6 39 9.3 No 9.5   87.2 11.8 25.9 No 10.6   76.4 26.7 22.3 No 11.8   131.7 18.4 34.6 No 12.9   120.2 19.6 11.6 No 13.2   171.3 39.7 37.7 Yes 19   198.9 49.4 60 Yes 23.7   17.2 4.1 31.6 No 5.9   11.7 36.9 45.2 Yes 7.3   97.2 1.5 30 No 9.6   100.4 9.6 3.6 No 10.7   276.7 2.3 23.7 No 11.8   136.2 19.2 16.6 No 13.2   137.9 46.4 59 Yes 19.2   210.8 49.6 37.7 Yes 23.8   19.4 16 22.3 No 6.6   19.6 20.1 17 Yes 7.6   43 25.9 20.5 No 9.6   36.9 38.6 65.6 No 10.8   112.9 17.4 38.6 No 11.9   240.1 7.3 8.7 No 13.2   193.7 35.4 75.6 Yes 19.2   296.4 36.3 100.9 Yes 23.8   7.8 38.9 50.6 No 6.6   38.2 3.7 13.8 Yes 7.6   97.5 7.6 7.2 No 9.7   39.5 41.1 5.8 No 10.8   117.2 14.7 5.4 No 11.9   85.7 35.8 49.3 Yes 13.3   217.7 33.5 59 Yes 19.4   261.3 42.7 54.7 Yes 24.2   18.7 12.1 23.4 No 6.7   17.9 37.6 21.6 No 8   62.3 12.6 18.3 No 9.7   73.4 17 12.9 No 10.9   234.5 3.4 84.8 No 11.9   139.3 14.5 10.2 No 13.4   219.8 33.5 45.1 Yes 19.6   281.4 39.6 55.8 Yes 24.4   27.5 1.6 20.7 No 6.9   53.5 2 21.4 No 8.1   66.9 11.7 36.8 No 9.7   38 40.3 11.9 No 10.9   262.9 3.5 19.5 No 12   225.8 8.2 56.5 No 13.4   166.8 42 3.6 Yes 19.6   220.3 49 3.2 Yes 24.7   18.8 21.7 50.4 No 7   50 11.6 18.4 No 8.4   59.6 12 43.1 No 9.7   129.4 5.7 31.3 No 11   76.3 27.5 16 Yes 12   232.1 8.6 8.7 No 13.4   229.5 32.3 74.2 Yes 19.7   266.9 43.8 5 Yes 25.4   25.1 25.7 43.3 No 8.5   94.2 4.9 8.1 Yes 9.7   116 7.7 23.1 Yes 11   139.2 14.3 25.6 No 12.2   68.4 44.5 35.6 No 13.6   255.4 26.9 5.5 Yes 19.8   289.7 42.3 51.2 Yes 25.4   66.1 5.8 24.2 No 8.6   75.5 10.8 6 Yes 9.9   134.3 4.9 9.3 No 11.2   206.8 5.2 19.4 No 12.2   102.7 29.6 8.4 No 14   220.5 33.2 37.9 Yes 20.1   243.2 49 44.3 Yes 25.4   16.9 43.7 89.4 No 8.7   43.1 26.7 35.1 Yes 10.1   69.2 20.5 18.3 No 11.3   218.5 5.4 27.4 No 12.2   175.7 15.4 2.4 No 14.1   262.7 28.8 15.9 No 20.2   283.6 42 66.2 Yes 25.5   90.4 0.3 23.2 No 8.7   44.7 25.8 20.6 Yes 10.1   75.3 20.3 32.5 No 11.3   239.8 4.1 36.9 No 12.3   120.5 28.5 14.2 No 14.2   248.4 30.2 20.3 Yes 20.2   287.6 43 71.8 Yes 26.2   56.2 5.7 29.7 No 8.7   149.8 1.3 24.3 Yes 10.1   199.8 3.1 34.6 No 11.4   109.8 14.3 31.7 No 12.4   172.5 18.1 30.7 No 14.4   293.6 27.7 1.8 Yes 20.7   276.9 48.9 41.8 Yes 27   26.8 33 19.3 No 8.8   140.3 1.9 9 Yes 10.3   96.2 14.8 38.9 No 11.4   67.8 36.6 114 No 12.5   164.5 20.9 47.4 Yes 14.5   238.2 34.3 5.3 Yes 20.7   80.2 0 9.2 Yes 8.8   139.5 2.1 26.6 No 10.3   107.4 14 10.9 No 11.5   237.4 5.1 23.5 No 12.5   147.3 23.9 19.1 No 14.6   184.9 43.9 1.7 Yes 20.7   23.8 35.1 65.9 Yes 9.2   222.4 3.4 13.1 No 11.5   75.1 35 52.7 No 12.6   78.2 46.8 34.5 No 14.6   273.7 28.9 59.7 Yes 20.8   224 2.4 15.6 No 11.6   165.6 10 17.6 No 12.6   74.7 49.4 45.7 No 14.7   182.6 46.2 58.7 No 21.2   48.3 47 8.5 No 11.6   265.2 2.9 43 Yes 12.7   187.9 17.2 17.9 No 14.7   292.9 28.3 43.2 No 21.4   121 8.4 48.7 Yes 11.6   290.7 4.1 8.5 Yes 12.8   227.2 15.8 49.9 No 14.8   228 37.7 32 No 21.5   197.6 3.5 5.9 No 11.7   177 9.3 6.4 Yes 12.8   280.2 10.1 21.4 No 14.8   213.5 43 33.8 No 21.7   222.4 4.3 49.8 No 11.7   175.1 22.5 31.5 No 14.9   241.7 38 23.2 No 21.8   168.4 7.1 12.8 No 11.7   188.4 18.1 25.6 No 14.9   170.2 7.8 35.2 No 11.7   142.9 29.3 12.6 No 15   284.3 10.6 6.4 Yes 15   193.2 18.4 65.7 No 15.2   123.1 34.6 12.4 No 15.2   93.9 43.5 50.5 No 15.3   228.3 16.9 26.2 No 15.5   184.9 21 22 No 15.5   141.3 26.8 46.2 No 15.5   187.8 21.1 9.5 Yes 15.6   239.3 15.5 27.3 Yes 15.7   240.1 16.7 22.9 No 15.9   209.6 20.6 10.7 No 15.9   125.7 36.9 79.2 No 15.9   286 13.9 3.7 No 15.9   110.7 40.6 63.2 No 16   280.7 13.9 37 No 16.1   202.5 22.3 31.6 No 16.6   197.6 23.3 14.2 No 16.6   109.8 47.8 51.4 Yes 16.7   163.3 31.6 52.9 Yes 16.9   213.4 24.6 13.1 Yes 17   177 33.4 38.7 No 17.1   215.4 23.6 57.6 No 17.1   135.2 41.7 45.9 No 17.2   191.1 28.7 18.2 No 17.3   149.7 35.6 6 No 17.3   214.7 24 4 Yes 17.4   265.6 20 0.3 Yes 17.4   253.8 21.3 30 Yes 17.6   218.4 27.7 53.4 Yes 18   131.1 42.8 28.9 Yes 18   163.5 36.8 7.4 Yes 18   199.1 30.6 38.7 Yes 18.3   210.7 29.5 9.3 Yes 18.4

Q: The dataset posted below lists a sample of months and the advertising budget (in hundreds of dollars) for TV, radio and newspaper advertisements. Also included is whether a coupon was published for that month and the resulting sales (in thousands of dollars). a) Develop a multiple regression model predicting the sales based off the four predictor variables: TV, radio, and newspaper advertising budget and whether a coupon is used.   Recode Coupon as 0 = No and 1 = Yes.   Report the estimated regression equation (Solve in Excel) TV ($100) radio ($100) newspaper ($100) Coupon sales ($1000) 0.7 39.6 8.7 No 1.6   230.1 37.8 69.2 No 22.1   4.1 11.6 5.7 Yes 3.2   44.5 39.3 45.1 No 10.4   250.9 36.5 72.3 No 22.2   8.6 2.1 1 No 4.8   17.2 45.9 69.3 Yes 9.3   104.6 5.7 34.4 No 10.4   216.8 43.9 27.2 Yes 22.3   5.4 29.9 9.4 No 5.3   69 9.3 0.9 No 9.3   70.6 16 40.8 No 10.5   151.5 41.3 58.5 No 18.5   195.4 47.7 52.9 Yes 22.4   13.1 0.4 25.6 Yes 5.3   76.4 0.8 14.8 No 9.4   156.6 2.6 8.3 No 10.5   180.8 10.8 58.4 No 12.9   248.8 27.1 22.9 No 18.9   216.4 41.7 39.6 Yes 22.6   7.3 28.1 41.4 Yes 5.5   8.7 48.9 75 No 7.2   95.7 1.4 7.4 No 9.5   199.8 2.6 21.2 Yes 10.6   206.9 8.4 26.4 No 12.9   237.4 27.5 11 No 18.9   205 45.1 19.6 Yes 22.6   13.2 15.9 49.6 No 5.6   25 11 29.7 No 7.2   31.5 24.6 2.2 No 9.5   89.7 9.9 35.7 Yes 10.6   57.5 32.8 23.5 No 11.8   88.3 25.5 73.4 No 12.9   204.1 32.9 46 Yes 19   239.9 41.5 18.5 Yes 23.2   8.4 27.2 2.1 No 5.7   28.6 1.5 33 No 7.3   25.6 39 9.3 No 9.5   87.2 11.8 25.9 No 10.6   76.4 26.7 22.3 No 11.8   131.7 18.4 34.6 No 12.9   120.2 19.6 11.6 No 13.2   171.3 39.7 37.7 Yes 19   198.9 49.4 60 Yes 23.7   17.2 4.1 31.6 No 5.9   11.7 36.9 45.2 Yes 7.3   97.2 1.5 30 No 9.6   100.4 9.6 3.6 No 10.7   276.7 2.3 23.7 No 11.8   136.2 19.2 16.6 No 13.2   137.9 46.4 59 Yes 19.2   210.8 49.6 37.7 Yes 23.8   19.4 16 22.3 No 6.6   19.6 20.1 17 Yes 7.6   43 25.9 20.5 No 9.6   36.9 38.6 65.6 No 10.8   112.9 17.4 38.6 No 11.9   240.1 7.3 8.7 No 13.2   193.7 35.4 75.6 Yes 19.2   296.4 36.3 100.9 Yes 23.8   7.8 38.9 50.6 No 6.6   38.2 3.7 13.8 Yes 7.6   97.5 7.6 7.2 No 9.7   39.5 41.1 5.8 No 10.8   117.2 14.7 5.4 No 11.9   85.7 35.8 49.3 Yes 13.3   217.7 33.5 59 Yes 19.4   261.3 42.7 54.7 Yes 24.2   18.7 12.1 23.4 No 6.7   17.9 37.6 21.6 No 8   62.3 12.6 18.3 No 9.7   73.4 17 12.9 No 10.9   234.5 3.4 84.8 No 11.9   139.3 14.5 10.2 No 13.4   219.8 33.5 45.1 Yes 19.6   281.4 39.6 55.8 Yes 24.4   27.5 1.6 20.7 No 6.9   53.5 2 21.4 No 8.1   66.9 11.7 36.8 No 9.7   38 40.3 11.9 No 10.9   262.9 3.5 19.5 No 12   225.8 8.2 56.5 No 13.4   166.8 42 3.6 Yes 19.6   220.3 49 3.2 Yes 24.7   18.8 21.7 50.4 No 7   50 11.6 18.4 No 8.4   59.6 12 43.1 No 9.7   129.4 5.7 31.3 No 11   76.3 27.5 16 Yes 12   232.1 8.6 8.7 No 13.4   229.5 32.3 74.2 Yes 19.7   266.9 43.8 5 Yes 25.4   25.1 25.7 43.3 No 8.5   94.2 4.9 8.1 Yes 9.7   116 7.7 23.1 Yes 11   139.2 14.3 25.6 No 12.2   68.4 44.5 35.6 No 13.6   255.4 26.9 5.5 Yes 19.8   289.7 42.3 51.2 Yes 25.4   66.1 5.8 24.2 No 8.6   75.5 10.8 6 Yes 9.9   134.3 4.9 9.3 No 11.2   206.8 5.2 19.4 No 12.2   102.7 29.6 8.4 No 14   220.5 33.2 37.9 Yes 20.1   243.2 49 44.3 Yes 25.4   16.9 43.7 89.4 No 8.7   43.1 26.7 35.1 Yes 10.1   69.2 20.5 18.3 No 11.3   218.5 5.4 27.4 No 12.2   175.7 15.4 2.4 No 14.1   262.7 28.8 15.9 No 20.2   283.6 42 66.2 Yes 25.5   90.4 0.3 23.2 No 8.7   44.7 25.8 20.6 Yes 10.1   75.3 20.3 32.5 No 11.3   239.8 4.1 36.9 No 12.3   120.5 28.5 14.2 No 14.2   248.4 30.2 20.3 Yes 20.2   287.6 43 71.8 Yes 26.2   56.2 5.7 29.7 No 8.7   149.8 1.3 24.3 Yes 10.1   199.8 3.1 34.6 No 11.4   109.8 14.3 31.7 No 12.4   172.5 18.1 30.7 No 14.4   293.6 27.7 1.8 Yes 20.7   276.9 48.9 41.8 Yes 27   26.8 33 19.3 No 8.8   140.3 1.9 9 Yes 10.3   96.2 14.8 38.9 No 11.4   67.8 36.6 114 No 12.5   164.5 20.9 47.4 Yes 14.5   238.2 34.3 5.3 Yes 20.7   80.2 0 9.2 Yes 8.8   139.5 2.1 26.6 No 10.3   107.4 14 10.9 No 11.5   237.4 5.1 23.5 No 12.5   147.3 23.9 19.1 No 14.6   184.9 43.9 1.7 Yes 20.7   23.8 35.1 65.9 Yes 9.2   222.4 3.4 13.1 No 11.5   75.1 35 52.7 No 12.6   78.2 46.8 34.5 No 14.6   273.7 28.9 59.7 Yes 20.8   224 2.4 15.6 No 11.6   165.6 10 17.6 No 12.6   74.7 49.4 45.7 No 14.7   182.6 46.2 58.7 No 21.2   48.3 47 8.5 No 11.6   265.2 2.9 43 Yes 12.7   187.9 17.2 17.9 No 14.7   292.9 28.3 43.2 No 21.4   121 8.4 48.7 Yes 11.6   290.7 4.1 8.5 Yes 12.8   227.2 15.8 49.9 No 14.8   228 37.7 32 No 21.5   197.6 3.5 5.9 No 11.7   177 9.3 6.4 Yes 12.8   280.2 10.1 21.4 No 14.8   213.5 43 33.8 No 21.7   222.4 4.3 49.8 No 11.7   175.1 22.5 31.5 No 14.9   241.7 38 23.2 No 21.8   168.4 7.1 12.8 No 11.7   188.4 18.1 25.6 No 14.9   170.2 7.8 35.2 No 11.7   142.9 29.3 12.6 No 15   284.3 10.6 6.4 Yes 15   193.2 18.4 65.7 No 15.2   123.1 34.6 12.4 No 15.2   93.9 43.5 50.5 No 15.3   228.3 16.9 26.2 No 15.5   184.9 21 22 No 15.5   141.3 26.8 46.2 No 15.5   187.8 21.1 9.5 Yes 15.6   239.3 15.5 27.3 Yes 15.7   240.1 16.7 22.9 No 15.9   209.6 20.6 10.7 No 15.9   125.7 36.9 79.2 No 15.9   286 13.9 3.7 No 15.9   110.7 40.6 63.2 No 16   280.7 13.9 37 No 16.1   202.5 22.3 31.6 No 16.6   197.6 23.3 14.2 No 16.6   109.8 47.8 51.4 Yes 16.7   163.3 31.6 52.9 Yes 16.9   213.4 24.6 13.1 Yes 17   177 33.4 38.7 No 17.1   215.4 23.6 57.6 No 17.1   135.2 41.7 45.9 No 17.2   191.1 28.7 18.2 No 17.3   149.7 35.6 6 No 17.3   214.7 24 4 Yes 17.4   265.6 20 0.3 Yes 17.4   253.8 21.3 30 Yes 17.6   218.4 27.7 53.4 Yes 18   131.1 42.8 28.9 Yes 18   163.5 36.8 7.4 Yes 18   199.1 30.6 38.7 Yes 18.3   210.7 29.5 9.3 Yes 18.4

College Algebra
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...
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Question

Q: The dataset posted below lists a sample of months and the advertising budget (in hundreds of dollars) for TV, radio and newspaper advertisements. Also included is whether a coupon was published for that month and the resulting sales (in thousands of dollars).

a) Develop a multiple regression model predicting the sales based off the four predictor variables: TV, radio, and newspaper advertising budget and whether a coupon is used.   Recode Coupon as 0 = No and 1 = Yes.   Report the estimated regression equation (Solve in Excel)

TV ($100) radio ($100) newspaper ($100) Coupon sales ($1000)
0.7 39.6 8.7 No 1.6  
230.1 37.8 69.2 No 22.1  
4.1 11.6 5.7 Yes 3.2  
44.5 39.3 45.1 No 10.4  
250.9 36.5 72.3 No 22.2  
8.6 2.1 1 No 4.8  
17.2 45.9 69.3 Yes 9.3  
104.6 5.7 34.4 No 10.4  
216.8 43.9 27.2 Yes 22.3  
5.4 29.9 9.4 No 5.3  
69 9.3 0.9 No 9.3  
70.6 16 40.8 No 10.5  
151.5 41.3 58.5 No 18.5  
195.4 47.7 52.9 Yes 22.4  
13.1 0.4 25.6 Yes 5.3  
76.4 0.8 14.8 No 9.4  
156.6 2.6 8.3 No 10.5  
180.8 10.8 58.4 No 12.9  
248.8 27.1 22.9 No 18.9  
216.4 41.7 39.6 Yes 22.6  
7.3 28.1 41.4 Yes 5.5  
8.7 48.9 75 No 7.2  
95.7 1.4 7.4 No 9.5  
199.8 2.6 21.2 Yes 10.6  
206.9 8.4 26.4 No 12.9  
237.4 27.5 11 No 18.9  
205 45.1 19.6 Yes 22.6  
13.2 15.9 49.6 No 5.6  
25 11 29.7 No 7.2  
31.5 24.6 2.2 No 9.5  
89.7 9.9 35.7 Yes 10.6  
57.5 32.8 23.5 No 11.8  
88.3 25.5 73.4 No 12.9  
204.1 32.9 46 Yes 19  
239.9 41.5 18.5 Yes 23.2  
8.4 27.2 2.1 No 5.7  
28.6 1.5 33 No 7.3  
25.6 39 9.3 No 9.5  
87.2 11.8 25.9 No 10.6  
76.4 26.7 22.3 No 11.8  
131.7 18.4 34.6 No 12.9  
120.2 19.6 11.6 No 13.2  
171.3 39.7 37.7 Yes 19  
198.9 49.4 60 Yes 23.7  
17.2 4.1 31.6 No 5.9  
11.7 36.9 45.2 Yes 7.3  
97.2 1.5 30 No 9.6  
100.4 9.6 3.6 No 10.7  
276.7 2.3 23.7 No 11.8  
136.2 19.2 16.6 No 13.2  
137.9 46.4 59 Yes 19.2  
210.8 49.6 37.7 Yes 23.8  
19.4 16 22.3 No 6.6  
19.6 20.1 17 Yes 7.6  
43 25.9 20.5 No 9.6  
36.9 38.6 65.6 No 10.8  
112.9 17.4 38.6 No 11.9  
240.1 7.3 8.7 No 13.2  
193.7 35.4 75.6 Yes 19.2  
296.4 36.3 100.9 Yes 23.8  
7.8 38.9 50.6 No 6.6  
38.2 3.7 13.8 Yes 7.6  
97.5 7.6 7.2 No 9.7  
39.5 41.1 5.8 No 10.8  
117.2 14.7 5.4 No 11.9  
85.7 35.8 49.3 Yes 13.3  
217.7 33.5 59 Yes 19.4  
261.3 42.7 54.7 Yes 24.2  
18.7 12.1 23.4 No 6.7  
17.9 37.6 21.6 No 8  
62.3 12.6 18.3 No 9.7  
73.4 17 12.9 No 10.9  
234.5 3.4 84.8 No 11.9  
139.3 14.5 10.2 No 13.4  
219.8 33.5 45.1 Yes 19.6  
281.4 39.6 55.8 Yes 24.4  
27.5 1.6 20.7 No 6.9  
53.5 2 21.4 No 8.1  
66.9 11.7 36.8 No 9.7  
38 40.3 11.9 No 10.9  
262.9 3.5 19.5 No 12  
225.8 8.2 56.5 No 13.4  
166.8 42 3.6 Yes 19.6  
220.3 49 3.2 Yes 24.7  
18.8 21.7 50.4 No 7  
50 11.6 18.4 No 8.4  
59.6 12 43.1 No 9.7  
129.4 5.7 31.3 No 11  
76.3 27.5 16 Yes 12  
232.1 8.6 8.7 No 13.4  
229.5 32.3 74.2 Yes 19.7  
266.9 43.8 5 Yes 25.4  
25.1 25.7 43.3 No 8.5  
94.2 4.9 8.1 Yes 9.7  
116 7.7 23.1 Yes 11  
139.2 14.3 25.6 No 12.2  
68.4 44.5 35.6 No 13.6  
255.4 26.9 5.5 Yes 19.8  
289.7 42.3 51.2 Yes 25.4  
66.1 5.8 24.2 No 8.6  
75.5 10.8 6 Yes 9.9  
134.3 4.9 9.3 No 11.2  
206.8 5.2 19.4 No 12.2  
102.7 29.6 8.4 No 14  
220.5 33.2 37.9 Yes 20.1  
243.2 49 44.3 Yes 25.4  
16.9 43.7 89.4 No 8.7  
43.1 26.7 35.1 Yes 10.1  
69.2 20.5 18.3 No 11.3  
218.5 5.4 27.4 No 12.2  
175.7 15.4 2.4 No 14.1  
262.7 28.8 15.9 No 20.2  
283.6 42 66.2 Yes 25.5  
90.4 0.3 23.2 No 8.7  
44.7 25.8 20.6 Yes 10.1  
75.3 20.3 32.5 No 11.3  
239.8 4.1 36.9 No 12.3  
120.5 28.5 14.2 No 14.2  
248.4 30.2 20.3 Yes 20.2  
287.6 43 71.8 Yes 26.2  
56.2 5.7 29.7 No 8.7  
149.8 1.3 24.3 Yes 10.1  
199.8 3.1 34.6 No 11.4  
109.8 14.3 31.7 No 12.4  
172.5 18.1 30.7 No 14.4  
293.6 27.7 1.8 Yes 20.7  
276.9 48.9 41.8 Yes 27  
26.8 33 19.3 No 8.8  
140.3 1.9 9 Yes 10.3  
96.2 14.8 38.9 No 11.4  
67.8 36.6 114 No 12.5  
164.5 20.9 47.4 Yes 14.5  
238.2 34.3 5.3 Yes 20.7  
80.2 0 9.2 Yes 8.8  
139.5 2.1 26.6 No 10.3  
107.4 14 10.9 No 11.5  
237.4 5.1 23.5 No 12.5  
147.3 23.9 19.1 No 14.6  
184.9 43.9 1.7 Yes 20.7  
23.8 35.1 65.9 Yes 9.2  
222.4 3.4 13.1 No 11.5  
75.1 35 52.7 No 12.6  
78.2 46.8 34.5 No 14.6  
273.7 28.9 59.7 Yes 20.8  
224 2.4 15.6 No 11.6  
165.6 10 17.6 No 12.6  
74.7 49.4 45.7 No 14.7  
182.6 46.2 58.7 No 21.2  
48.3 47 8.5 No 11.6  
265.2 2.9 43 Yes 12.7  
187.9 17.2 17.9 No 14.7  
292.9 28.3 43.2 No 21.4  
121 8.4 48.7 Yes 11.6  
290.7 4.1 8.5 Yes 12.8  
227.2 15.8 49.9 No 14.8  
228 37.7 32 No 21.5  
197.6 3.5 5.9 No 11.7  
177 9.3 6.4 Yes 12.8  
280.2 10.1 21.4 No 14.8  
213.5 43 33.8 No 21.7  
222.4 4.3 49.8 No 11.7  
175.1 22.5 31.5 No 14.9  
241.7 38 23.2 No 21.8  
168.4 7.1 12.8 No 11.7  
188.4 18.1 25.6 No 14.9  
170.2 7.8 35.2 No 11.7  
142.9 29.3 12.6 No 15  
284.3 10.6 6.4 Yes 15  
193.2 18.4 65.7 No 15.2  
123.1 34.6 12.4 No 15.2  
93.9 43.5 50.5 No 15.3  
228.3 16.9 26.2 No 15.5  
184.9 21 22 No 15.5  
141.3 26.8 46.2 No 15.5  
187.8 21.1 9.5 Yes 15.6  
239.3 15.5 27.3 Yes 15.7  
240.1 16.7 22.9 No 15.9  
209.6 20.6 10.7 No 15.9  
125.7 36.9 79.2 No 15.9  
286 13.9 3.7 No 15.9  
110.7 40.6 63.2 No 16  
280.7 13.9 37 No 16.1  
202.5 22.3 31.6 No 16.6  
197.6 23.3 14.2 No 16.6  
109.8 47.8 51.4 Yes 16.7  
163.3 31.6 52.9 Yes 16.9  
213.4 24.6 13.1 Yes 17  
177 33.4 38.7 No 17.1  
215.4 23.6 57.6 No 17.1  
135.2 41.7 45.9 No 17.2  
191.1 28.7 18.2 No 17.3  
149.7 35.6 6 No 17.3  
214.7 24 4 Yes 17.4  
265.6 20 0.3 Yes 17.4  
253.8 21.3 30 Yes 17.6  
218.4 27.7 53.4 Yes 18  
131.1 42.8 28.9 Yes 18  
163.5 36.8 7.4 Yes 18  
199.1 30.6 38.7 Yes 18.3  
210.7 29.5 9.3 Yes 18.4  
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