Engine Type Capacity Maintenance cost Odometer Miles Miles ID Manufacturer Engine Type (0=diesel) Age 5 54375 11973 10 Keiser Gasoline 14 4646 1072 2 21858 11969 396 Thompson Diese 14 10 116580 11967 122 Bluebird Gasoline 55 9394 2 11948 Keiser 14 1078 22444 751 Diesel 55 1008 2 22672 11925 279 Bluebird Diesel 55 5329 5 50765 11922 500 Bluebird Gasoline 520 Bluebird Diesel 55 4794 10 119130 11896 55 3952 8 37872 11883 759 Keiser Diesel 42 3742 7 73703 11837 714 Bluebird Diesel 875 Bluebird Diese 55 4376 9 97947 11814 55 4832 10 119860 11800 600 Bluebird Diesel 5160 11798 953 Diesel 55 10 117700 Bluebird 55 1955 4 41096 11789 101 Bluebird Diesel 6 70086 11782 358 Bluebird Diesel 55 2775 55 5352 69438 11781 29 Bluebird Gasoline 55 3065 63384 11778 365 Keiser Diesel 11758 162 Keiser Gasoline 55 3143 31266 34674 11757 686 Bluebird Diesel 55 1569 V Y W DO DO W W O O O 370 Keiser Gasoline 55 7766 86528 11707 55 374 93672 11704 887 Bluebird Diesel O O O H O O O O O H O H H O O H H O O H O H O H O H O O O O O O O O H O O H O P 464 Bluebird Gasoline 55 2540 34530 11698 948 Keiser Diesel 42 4342 97956 11691 75229 Keiser Diese 55 3361 11668 578 481 Keiser Gasoline 6 3097 34362 11662 8263 102969 11615 43 Bluebird Gasoline 55 55 4218 83424 11610 704 Bluebird Diesel 40824 11576 814 Bluebird Diesel 55 2028 39 Bluebird 5821 69444 11533 Gasoline 55 98307 11518 699 Bluebird Gasoline 55 9069 71970 11462 75 Bluebird Diesel 55 3011 693 Keiser Gasoline 55 9193 101889 11461 106605 989 Keiser Diese 55 4795 11418 505 10276 11359 982 Bluebird Diesel 55 70122 11358 321 Bluebird Diesel 42 2732 91968 11344 724 Keiser Diesel 42 3754 101196 11342 732 Keiser Diesel 42 4640 3410 97065 11336 880 Keiser Gasoline 55 14 5922 128711 11248 193 Thompson Diesel 11231 884 Bluebird Diesel 55 4364 92457 79240 11222 57 Bluebird Diesel 55 3190 Diesel 42 3213 68526 11168 731 BluebirdDiesel 11148 61 Keiser 55 4139 103536 135 Bluebird Diesel 55 3560 76426 11127 11112 833 Thompson Diesel 14 3920 90968 00 00 00 ~ LO 671 Thompson Gasoline 14 6733 89792 11100 Bluebird 55 11048 692 Diesel 3770 93248 Bluebird Diesel 55 5168 10 103700 11018 200 Diesel 14 7380 146860 11003 754 Keiser 14 540 Bluebird Gasoline 55 3656 4 45284 10945 Bluebird Gasoline 55 6213 6 64434 10911 660 Gasoline 4 45744 10902 353 Keiser 55 4279 482 Bluebird Gasoline 55 10575 10 116534 10802 6 9 10802 868 Thompson Diesel 4752 95922 984 Bluebird Diesel 55 3809 8 87664 10760 977 Bluebird Diesel 55 3769 7 79422 10759 10755 Keiser Diesel 4 47596 705 42 2152 767 Keiser Diesel 55 2985 6 71538 10726 326 Bluebird Diesel 55 4563 9 107343 10724 42 4723 10674 120 Keiser Diesel 10 110320 44604 10662 554 Bluebird Diesel 42 1826 4 Bluebird Diesel 55 1061 2 23152 10633 695 OH OH OOH OOH OOH H H OOHH OOO OOO OOO HH HH OOOHOOO 9 Keiser Gasoline 55 3527 4 46848 10591 Gasoline 9669 10 106040 10551 861 Bluebird 55 Keiser Diesel 14 2116 4 44384 10518 603 156 Thompson Diesel 14 6212 12 140460 10473 55 7 73423 427 Keiser Gasoline 6927 10355 Bluebird Gasoline 55 1881 2 20742 10344 883 168 Thompson Gasoline 14 7004 7 83006 10315 Bluebird Diesel 42 5284 10 101000 10235 954 71778 10227 768 Bluebird Diesel 42 3173 7 490 Bluebird Gasoline 55 10133 10 106240 10210 Bluebird 55 2356 5 57065 10209 725 Diesel 10167 45 Keiser Diesel 55 3124 6 60102 10140 38 Keiser Gasoline 14 5976 6 61662 6 5408 11 128117 10128 314 Thompson Diesel Bluebird Diesel 55 3690 7 10095 507 72849 40 Bluebird Gasoline 55 9573 10 118470 10081 918 Bluebird Diesel 55 2470 5 53620 10075 89960 10055 387 Bluebird Gasoline 55 6863 8 418 Bluebird Diesel 55 4513 104715 100003. Refer to the Lincolnville School District bus data. Consider a regression a) In addition to the engine dummy variable construct manufacturer dummy variables. (Hint: Since there are 3 manufacturers, you need 2 dummy variables. One takes a value of 1 if the manufacturer is Keiser and o if the manufacturer is Thompson or Bluebird and a second takes a value of 1 if the manufacturer is Thompson and o if the manufacturer is Keiser or Bluebird. Note: Having 3 dummies for 3 manufacturers would create multicollinearity.) b) Suppose you are considering a regression where maintenance cost is the dependent variable and the potential independent variables are manufacturer (both dummy variables, engine type, age, odometer miles, and capacity.) Create a correlation matrix. Are there any variables you think cannot be in a regression together? c) Use a statistical software package to determine the multiple regression equation. (Use your conclusions from the correlation matrix to omit independent variables, if necessary.) d) Show that your regression equation shows a significant relationship (i.e. we can reject the null that all coefficients are o.) e) Write out the regression equation and interpret its practical application. f) Report and interpret the R-square. g) Develop a histogram of the residuals from the final regression equation. Is it reasonable to conclude that the normality assumption has been met? h) Plot the residuals against the fitted values of Y from the final regression equation. Plot the residuals on the vertical axis and the fitted values on the horizontal axis. Use the graph to explain whether you think the linearity and homoskedasticity assumptions hold