35. Predicting Repair Time. Refer to the Johnson Filtration problem introduced in this sec- tion. Suppose that in addition to information on the number of months since the machine was serviced and whether a mechanical or an electrical repair was necessary, the managers obtained a list showing which repairperson performed the service. The revised data follow. Repair Time in Hours Repairperson Months Since Last Service Type of Repair 2.9 2 Electrical Dave Newton 3.0 6 Mechanical 4.8 8 1.8 3 Electrical Mechanical Dave Newton Bob Jones Dave Newton 2.9 2 4.9 7 4.2 4.8 6648 Electrical Dave Newton Electrical Bob Jones 9 Mechanical Bob Jones Mechanical Bob Jones 4.4 4 Electrical Bob Jones 4.5 6 Electrical Dave Newton a. Ignore for now the months since the last maintenance service (x,) and the repair- person who performed the service. Develop the estimated simple linear regression equation to predict the repair time (y) given the type of repair (x2). Recall that x2 = 0 if the type of repair is mechanical and 1 if the type of repair is electrical. b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. c. Ignore for now the months since the last maintenance service and the type of repair associated with the machine. Develop the estimated simple linear regression equa- tion to predict the repair time given the repairperson who performed the service. Let x3 = 0 if Bob Jones performed the service and x = 1 if Dave Newton performed the service. d. Does the equation that you developed in part (c) provide a good fit for the observed data? Explain