A statistical program is recommended. A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. Repair Time in Hours Months Since 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 Mechanical Dave Newton 2.5 2 Electrical Dave Newton 4.9 7 Electrical Bob Jones 4.6 Mechanical Bob Jones 4.8 Mechanical Bob Jones 4.4 4 Electrical Bob Jones 4.5 Electrical 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 (xɔ). Let x, = 0 if the type of repair is mechanical and x, = 1 if the type of repair is electrical. (Round your numerical values to three decimal places.) ŷ = 3.550 + .450x
A statistical program is recommended. A company provides maintenance service for water-filtration systems throughout southern Florida. Customers contact the company with requests for maintenance service on their water-filtration systems. To estimate the service time and the service cost, the company's managers want to predict the repair time necessary for each maintenance request. Hence, repair time in hours is the dependent variable. Repair time is believed to be related to three factors, the number of months since the last maintenance service, the type of repair problem (mechanical or electrical), and the repairperson who performed the service. Data for a sample of 10 service calls are reported in the table below. Repair Time in Hours Months Since 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 Mechanical Dave Newton 2.5 2 Electrical Dave Newton 4.9 7 Electrical Bob Jones 4.6 Mechanical Bob Jones 4.8 Mechanical Bob Jones 4.4 4 Electrical Bob Jones 4.5 Electrical 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 (xɔ). Let x, = 0 if the type of repair is mechanical and x, = 1 if the type of repair is electrical. (Round your numerical values to three decimal places.) ŷ = 3.550 + .450x
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 11PPS
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