a. Ignore for now the months since the last maintenance service (¤1 ) and the repairperson who performed the ser estimated simple linear regression equation to predict the repair time (y) given the type of repair (2 ). Recall that 22 = 0 if the type of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals). Time = Туре b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. (to 4 decimals) No because the p-value of shows that the relationship is not significant v for any reasonable value of a. 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 equation to predict the repair time given the repairperson who performed the service. Let 23 =0 if Bob Jones performed the service and #3 = 1 if Dave Newton performed the service (to 2 decimals). Enter negative value as negative number. Time = Person d. Does the equation that you developed in part (c) provide a good fit for the observed data? Explain.

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Johnson Filtration, Inc. provides maintenance service for water-filtration systems. 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.
Click on the datafile logo to reference the data.
DATA file
Repair Time
Months Since
in Hours
Last Service
Type of Repair
Repairperson
2.9
Electrical
Dave Newton
3.0
Mechanical
Dave Newton
4.8
8.
Electrical
Bob Jones
1.8
3
Mechanical
Dave Newton
2.9
2
Electrical
Dave Newton
4.9
Electrical
Bob Jones
4.2
6.
Mechanical
Bob Jones
4.8
8.
Mechanical
Bob Jones
4.4
Electrical
Bob Jones
4.5
Electrical
Dave Newton
a. Ignore for now the months since the last maintenance service (1) 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 (2 ). Recall that a = 0 if the type
of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals).
Time =
Туре
b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. (to 4 decimals)
No
because the p-value of
shows that the relationship is not significant
reasonable value of a.
v for any
eAssignmentMain.do?takeAssignmentSessionLocator=assignment-take.be934haf-ef95-13hc 200d 1ad0
Transcribed Image Text:Johnson Filtration, Inc. provides maintenance service for water-filtration systems. 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. Click on the datafile logo to reference the data. DATA file Repair Time Months Since in Hours Last Service Type of Repair Repairperson 2.9 Electrical Dave Newton 3.0 Mechanical Dave Newton 4.8 8. Electrical Bob Jones 1.8 3 Mechanical Dave Newton 2.9 2 Electrical Dave Newton 4.9 Electrical Bob Jones 4.2 6. Mechanical Bob Jones 4.8 8. Mechanical Bob Jones 4.4 Electrical Bob Jones 4.5 Electrical Dave Newton a. Ignore for now the months since the last maintenance service (1) 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 (2 ). Recall that a = 0 if the type of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals). Time = Туре b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. (to 4 decimals) No because the p-value of shows that the relationship is not significant reasonable value of a. v for any eAssignmentMain.do?takeAssignmentSessionLocator=assignment-take.be934haf-ef95-13hc 200d 1ad0
a. Ignore for now the months since the last maintenance service (1 ) and the repairperson who performed the service. Develop the
%3D
estimated simple linear regression equation to predict the repair time (y) given the type of repair (a2 ). Recall that 2 = 0 if the type
of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals).
Time
Туре
b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. (to 4 decimals)
No
because the p-value of
shows that the relationship is not significant
v for any
reasonable value of a.
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 equation to predict the repair time given the repairperson who performed the service. Let 23 = 0 if
Bob Jones performed the service and Is =1 if Dave Newton performed the service (to 2 decimals). Enter negative value as negative
number.
Time =
Person
d. Does the equation that you developed in part (c) provide a good fit for the observed data? Explain.
Repairperson is a better predictor of repair time than the type of repair v
Transcribed Image Text:a. Ignore for now the months since the last maintenance service (1 ) and the repairperson who performed the service. Develop the %3D estimated simple linear regression equation to predict the repair time (y) given the type of repair (a2 ). Recall that 2 = 0 if the type of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals). Time Туре b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. (to 4 decimals) No because the p-value of shows that the relationship is not significant v for any reasonable value of a. 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 equation to predict the repair time given the repairperson who performed the service. Let 23 = 0 if Bob Jones performed the service and Is =1 if Dave Newton performed the service (to 2 decimals). Enter negative value as negative number. Time = Person d. Does the equation that you developed in part (c) provide a good fit for the observed data? Explain. Repairperson is a better predictor of repair time than the type of repair v
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