Q7

Refer to the Lincolnville School District bus data. First, add a variable to change the type of engine (diesel or gasoline) to a qualitative variable. If the engine type is diesel, then set the qualitative variable to 0. If the engine type is gasoline, then set the qualitative variable to 1. Develop a regression equation using statistical software with maintenance cost as the dependent variable and age, odometer miles, miles since last maintenance, and engine type as the independent variables. Develop a correlation matrix. (Negative amounts should be indicated by a minus sign. Round your answers to 4 decimal places.) Maintenance cost (S) Age (years) Odometer Miles Miles since last Maintenance Maintenance cost ($) Age (years) Odometer Miles Miles since last Maintenance Which independent variables have strong or weak correlations with the dependent variable? There is a correlation between age and maintenance cost. Do you see any problems with multicollinearity? O Yes ON Use a statistical software package to determine the multiple regression equation. Maintenance Costs = Age. Use a statistical software package to determine the multiple regression equation. (Negative amounts should be indicated by a minus sign. Round your answers to 3 decimal places.) Maintenance Costs = Age + Engine type. What is the value of RZ. (Round your answer to 1 decimal place.) R2 % Develop a histogram of the residuals from the final regression equation. Which histogram is correct? Histogram of the residuals 1 Histogram of the residuals 2 Histogram of the residuals 3 Histogram Histogram Histogram 35 30 30 25 25 20 Frequency Frequency 15 10 5 1375 -825 5 -275 325 875 1425 1975 -1375 -825 -275 3 325 875 1425 1975 1375 -825 -275 325 875 1425 1975 Bin Bin Bin O Histogram of the residuals 1 O Histogram of the residuals 2 O Histogram of the residuals 3 Is it reasonable to conclude that the normality assumption has been met? Yes No Plot the residuals against the fitted values from the final regression equation with the residuals on the vertical axis and the fitted values on the horizontal axis. Which plot is correct? Residuals vs Fits 1 Residuals vs Fits 2 Residuals vs Fits 3 Residuals Residuals Residuals O Residuals vs Fits 1 O Residuals vs Fits 2 O Residuals vs Fits 3