Question

Please Use Excel To Show All Work, I will like your asnwer if you do this :)

15.35 Refer to the Johnson Filtration problem introduced in this section. 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 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	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

1. Clearly specify the dependent variable and the independent variables, and develop an estimated regression equation that can be used to predict the Repair Time given Months Since Last Service, Type of Repair, and Repairperson.
2. What are the estimates for parameters of the independent variables?
3. What are the p-values of the t tests for the independent variables?
4. What is the p-value of the F test?
5. At the .05 level, are there significant relationship between the dependent variable and the independent variables?
6. What is the multiple coefficient of determination?
7. What is the adjusted multiple coefficient of determination?
8. Interpret the results.

Answer 1

The setup is:

Now, running the regression analysis,

We get the output as follows:

(a) The dependent variable is Repair Time and the independent variables are Months Since Last Service, Type of Repair, and Repairperson.

(b) The estimates are:

	Coefficients
Intercept	1.860160428
Months Since Last Service	0.29144385
Type of Repair	1.102406417
Repairperson	-0.60909091

(c)

	P-value
Intercept	0.043318538
Months Since Last Service	0.01304298
Type of Repair	0.010910551
Repairperson	0.167444241

(d) The p-value of the F test is 0.002091.

(e) Since the p-value (0.002091) is less than the significance level (0.05), we can reject the null hypothesis.

Therefore, we can conclude that there is a significant relationship between the dependent variable and the independent variables.

(f) The multiple coefficient of determination is 0.900199692.

(g) The adjusted multiple coefficient of determination is 0.850299539.

(h) The model is significant and there is a linear relationship between Repair Time and Months Since Last Service, Type of Repair, and Repairperson.

Repair Time	Months Since Last Service	Type of Repair	Repairperson
2.9	2	1	1
3	6	0	1
4.8	8	1	0
1.8	3	0	1
2.9	2	1	1
4.9	7	1	0
4.2	9	0	0
4.8	8	0	0
4.4	4	1	0
4.5	6	1	1