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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.


Repair Time Months Since in Hours Last Service Type of Repair Repairperson 2. 9 2 Electrical Dave Newton 3. 0 6 Mechanical Dave Newton 4. 8 8 Electrical Bob Jones 1. 8 3 Mechanical Dave Newton 2. 9 2 Electrical Dave Newton 4. 9 7 Electrical Bob Jones 4. 2 9 Mechanical Bob Jones 4. 8 8 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 (x1) 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 x2 = 0 if the type of repair is mechanical and 1 if the type of repair is electrical (to 2 decimals).


Time =. +. Type


b. Is type of repair a good predictor of the repair time?


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 x3 = 0 if Bob Jones performed the service and x3 = 1 if Dave Newton performed the service (to 2 decimals).


Time =. -. Person


d. Compare your results from parts (a) and (c). What can you conclude?


Who is the faster repairperson?

Sagot :

The estimated simple linear regression equation to predict the repair time is Time = 3.45 + 0.617type.

What is linear regression?

It should be noted that linear regression simply means a set of statistical process that shows the relationship between the independent and dependent variables.

Here, the estimated simple linear regression equation to predict the repair time is Time = 3.45 + 0.617type.

The value of R² is 0.087. This illustrates that the type of repair is not a good predictor of the repair time.

Also, the estimated simple linear regression equation to predict the repair time given the repairperson is Time = 4.62 - 1.60person. It can be concluded that the tye of repair and time is positively correlated.

Learn more about regression on:

https://brainly.com/question/25987747

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