Question

In: Statistics and Probability

Salary Years Age MBA? 35600 7.3 33 0 71100 24.1 61 0 42300 8.6 35 1...

Salary	Years	Age	MBA?
35600	7.3	33	0
71100	24.1	61	0
42300	8.6	35	1
51200	11.5	43	1
41300	13.8	40	0
64900	18.1	55	0
54600	16.9	49	0
43800	9.4	37	1
46600	12.2	48	1
50100	16	50	0
32800	4.2	28	1
49300	11.5	49	0
38100	7.3	35	1
53500	14.4	52	1
46000	10.8	45	0

The data in the above table give the annual salary (Salary), number of years of employment (Years), employee's age (Age), and whether or not the employee has an MBA degree (1 = yes, 0 = no) for 15 workers in a particular industry and location.

In this location and industry, what is the predicted salary of a 40 year old employee who has 10 years of employment and holds an MBA degree? Use the MLR equation.

Question 7 options:

	about $44,590
	about $79,140
	about $28,590
	about $63150
	about 35500

Salary	Years	Age	MBA?
35600	7.3	33	0
71100	24.1	61	0
42300	8.6	35	1
51200	11.5	43	1
41300	13.8	40	0
64900	18.1	55	0
54600	16.9	49	0
43800	9.4	37	1
46600	12.2	48	1
50100	16	50	0
32800	4.2	28	1
49300	11.5	49	0
38100	7.3	35	1
53500	14.4	52	1
46000	10.8	45	0

The data in the above table give the annual salary (Salary), number of years of employment (Years), employee's age (Age), and whether or not the employee has an MBA degree (1 = yes, 0 = no) for 15 workers in a particular industry and location.

At the 0.10 level of significance, are any of the predictor variables making a statistically significant contribution to predicting Salary?

Question 8 options:

	Yes -- both MBA? and Age make statistically significant contributions to predicting Salary.
	Yes -- ALL THREE variables make statistically significant contributions to predicting Salary.
	Yes -- both Years and MBA? make statistically significant contributions to predicting Salary.
	No -- none of the three make a statistically significant contribution to predicting Salary.
	Yes -- both Years and Age make statistically significant contributions to predicting Salary.
	Yes -- Age makes a statistically significant contribution to predicting Salary.
	Yes -- Years makes a statistically significant contribution to predicting Salary.
	Yes -- MBA? makes a statistically significant contribution to predicting Salary.

Expert Solution

Using Minitab:

Click Stat > Regression > Regression... on the top menu, as shown below:

You will be presented with the following Regression dialogue box:

Click the OK button. The MLR output that Minitab produces is shown below.

for age=40, years = 10 and mba = 1

Salary = 9086 + 1152 *10 + 533 *40 + 2654 *1 =44590

From the above table, the results can be summarized as follows:

· MBA is not a significant coefficient (P = 0.228) (P-value > 0.1)and does not have a significant interaction with any other predictor.

· Age is a significant coefficient (P = 0.06). (P-value < 0.1)

· Years is a significant coefficient (P = 0.04).(P-value < 0.1)

Yes -- both Years and Age make statistically significant contributions to predicting Salary.

Hope this will be helpful. Thanks and God Bless You :)

orchestra answered 2 years ago

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