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35. Refer to the Johnson Filtration problem introduced in this section. Suppose that in addi- tion to information on the number of months since the

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35. Refer to the Johnson Filtration problem introduced in this section. Suppose that in addi- tion to information on the number of months since the machine was serviced and whether we a mechanical or an electrical repair was necessary, the managers obtained a list showing which repairperson performed the service. The revised data follow. the ns C Repair Time Months Since in Hours Last Service Type of Repair Repairperson gion 2.9 Electrical Dave Newton ex- WEB file 3.0 Mechanical Dave Newton | 4.8 Electrical Bob Jones D Repair 1.8 Mechanical Dave Newton 2.9 Electrical Dave Newton 4.9 Electrical Bob Jones 4.2 Mechanical Bob Jones 4.8 Mechanical Bob Jones 4.4 Electrical Bob Jones 45 Electrical Dave Newton a. Ignore for now the months since the last maintenance service (x) and the repairperson dent 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 le? of repair is mechanical and 1 if the type of repair is electrical. ile? b. Does the equation that you developed in part (a) provide a good fit for the observed data? Explain. lent c. Ignore for now the months since the last maintenance service and the type of repair as- 12. 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. Does the equation that you developed in part (c) provide a good fit for the observed data? Explain. 36. This problem is an extension of the situation described in exercise 35. Economics 326 Assignment #4 Please use statistical software (Excel, for example) to estimate sample multiple regression line. For all problems, please write down the estimated sample regression lines in the standard format, and explain the meaning of coefficient of determination or R Square, as well as the meaning of each and all estimated coefficients (including the intercept) in the context of each problem and in plain English. Set #1 Page 705, problems 24 and 25 Set #2 Page 715, problems 35, 36, and 37 Set #3 Page 842, problems 30, 31

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