35. Refer to the Johnson Filtration example introduced in this section. Suppose that in addi- tion to information on the number of months since the machine was serviced and whether a mechanical or an electrical repair had occurred, the managers obtained a list showing which repairperson performed the service. The revised data follow. Repair Time in Hours Months Since Last Service Repairperson 2683N79640 2.9 3.0 4.8 1.8 9968 2.9 4.9 4.2 4.8 4.4 4.5 Type of Repair Electrical Mechanical Electrical Mechanical Dave Newton Dave Newton Bob Jones Dave Newton Electrical Electrical Dave Newton Bob Jones Mechanical Bob Jones Mechanical Bob Jones Electrical Electrical Bob Jonest Dave Newton

a. Ignore for now the months since the last maintenance service (x)) and the repairperson 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 x = 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 as- sociated with the machine. Develop the estimated simple linear regression equation to predict the repair time given the repairperson who performed the service. Let x = 0 if Bob Jones performed the service and x3 = 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.