3. 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 0 if the

manufacturer is Thompson or Bluebird and a second takes a value of 1 if the manufacturer is Thompson and 0 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.)

4. d) Show that your regression equation shows a significant relationship (i.e. we can reject the null that all coefficients are 0.)

5. e) Write out the regression equation and interpret its practical application.

6. f) Report and interpret the R-square.

7. g) Develop a histogram of the residuals from the final

   regression equation. Is it reasonable to conclude that

   the normality assumption has been met?

8. 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

Engine Type (O=diesel Capacity 14 14 EE ? 59 9 42 5: 55 55 55 5. 50 5 mm en NSNN 9. Om mo 1 5 55 50 101 358 29 365 162 686 370 887 464 948 678 481 43 704 0012180198119821 291 292 293 ADE 8 Miles 11973 11969 11967 11948 11925 11922 11890 11883 11837 11814 11800 11798 11789 11782 11781 11778 11758 11757 11707 11704 11698 11691 11668 11662 11615 11610 11576 11533 11518 11462 11461 11418 11359 11358 11344 11342 11342 11336 11248 11231 11222 11168 B&B MO!||||||!!!!!||||||||| - 6 e 0 4 6 0 1 55 55 55 50 ED EE 43 74 982 321 724 100 134 800 193 1 42 59 14 09 NLD 0 0 9 7 8 61 135 833 671 692 200 754 540 660 0 1 0 0 0 8 8 10 14 1 4 6 1 353 1 482 1 4 10 14 9 8 0 0 0 7 4 A 0 0 0 0 6 6 9 10 Kelser Bluebird Thompson Thompson Bluebird Bluebird Kelser was Bluebird end Bluebird Kelser mated Bluebird Thompson Bluebird Bluebird Kelser Keiser Bluebird Kolser Kelser Blushird Bluebird Bluebird Kelser ole Bluebird Kelser Thompson . 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Om mo 1 5 55 50 101 358 29 365 162 686 370 887 464 948 678 481 43 704 0012180198119821 291 292 293 ADE 8 Miles 11973 11969 11967 11948 11925 11922 11890 11883 11837 11814 11800 11798 11789 11782 11781 11778 11758 11757 11707 11704 11698 11691 11668 11662 11615 11610 11576 11533 11518 11462 11461 11418 11359 11358 11344 11342 11342 11336 11248 11231 11222 11168 B&B MO!||||||!!!!!||||||||| - 6 e 0 4 6 0 1 55 55 55 50 ED EE 43 74 982 321 724 100 134 800 193 1 42 59 14 09 NLD 0 0 9 7 8 61 135 833 671 692 200 754 540 660 0 1 0 0 0 8 8 10 14 1 4 6 1 353 1 482 1 4 10 14 9 8 0 0 0 7 4 A 0 0 0 0 6 6 9 10 Kelser Bluebird Thompson Thompson Bluebird Bluebird Kelser was Bluebird end Bluebird Kelser mated Bluebird Thompson Bluebird Bluebird Kelser Keiser Bluebird Kolser Kelser Blushird Bluebird Bluebird Kelser ole Bluebird Kelser Thompson . Keiser Bluebird olubic Thompson Bluebird Bluebird Bluebird Bluebird va Kelser . Keiser Thompson Bluebird Bluebird Bluebird Bluebird Bluebird Diesel Diesel Diesel Gasoline Diesel c! Diesel Diesel Gasoline Gasoline Gasoline Gasoline dsome Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel Diesel ni... Diesel Die Diesel Corolla Gasoline Colin Gasoline Diesel Diesel Gasoline Gasoline Gasoline Diesel Diesel Gasoline Die Diesel local Diesel Gasoline Diesel . 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