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# Regression analysis in SAS

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Problem

A high-tech company wants to study the relationship between salary (Y) and some factors such as degree obtained (1=bachelor's degree, 2=master's degree. 3=doctoral degree), year of experience, and the number of persons currently supervised. The data is given as follows. The first column denotes the salary (in thousands), the second column denotes the degree obtained, the third column denotes year of experience, and the fourth column denotes the number of persons supervised.

The decision maker needs you to provide him/her with an appropriate model so that he/she can determine the new employee's salary in the future. Analyze the data, give the model, and justify the appropriateness of your model. How do you explain the decision maker how to use your model?

You are encouraged to study the new chapters, i.e., chapter 9-12 of Applied Linear Regression Models 4th edition, by Kutner et al and perform the relevant correct analysis for the given problem. Using SAS is highly encouraged.

Data
Y X1 X2 X3
62.8 2 5.49 2
36.8 1 2.82 0
163.7 3 29.54 42
78.0 3 8.92 3
65.5 3 0.14 0
82.0 2 15.76 4
34.0 1 2.27 0
29.7 1 1.20 0
86.1 2 6.33 3
70.6 3 15.74 0
74.2 1 22.46 6
44.1 1 4.16 0
31.6 1 2.62 0
65.5 1 15.06 5
57.2 3 2.92 0
60.3 3 2.26 0
43.8 1 10.76 2
76.5 3 14.71 4
120.1 3 21.76 10
85.9 3 15.63 8
55.9 3 1.17 0
44.3 2 2.33 0
79.9 3 17.10 18
56.5 2 8.45 1
57.3 3 4.55 0
61.0 2 14.39 8
52.2 2 5.78 3
45.7 2 2.08 1
44.8 2 1.44 0
39.1 2 1.00 0
68.1 2 10.53 7
48.2 2 19.23 0
51.0 2 5.18 2
45.7 1 4.43 1
51.4 2 3.04 2
40.9 2 1.02 1
57.7 1 10.14 5
95.5 3 26.53 8
34.9 1 6.49 3
66.6 2 13.97 7
30.0 1 4.18 0
64.9 3 12.88 6
151.2 2 16.01 28
72.4 2 11.13 6
41.8 2 0.71 0
57.8 3 1.55 0
72.7 3 3.92 1
36.1 1 4.37 1
39.8 2 0.79 0
29.0 1 0.65 0
40.4 2 0.69 0
40.7 2 1.09 0
41.7 2 1.58 0
97.2 3 10.89 8
85.3 2 21.08 0
42.6 2 7.00 0
39.1 1 4.09 0
46.6 2 8.86 1
53.9 2 11.05 6
87.4 3 2.37 13
81.7 3 6.37 0
42.5 1 8.00 0
40.0 2 0.44 0
60.5 3 2.10 0
104.8 3 19.81 24