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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

https://brainmass.com/statistics/regression-analysis/245470

#### Solution Summary

The solution provides step by step method for the calculation of regression model in SAS. SAS code, results and interpretations are also given .

\$2.19

## File SAS and conduct a multiple linear regression analysis

For this assignment, you will use the attached dataset, Airlines_Week_1. You will read the file into SAS and conduct a multiple linear regression analysis.

The following steps are necessary to complete this assignment:

1. Read an Excel file into SAS and list the contents of the SAS dataset (Use Proc Contents). Note that there are no missing values in the dataset.
2. Variable I is the airline ID, T is the year, Q is the output in revenue passenger miles, C is the total cost in \$1,000, PF is the fuel price, and LF is the load factor, which is the average capacity utilization of the fleet. For this assignment, ignore variables I and T. Your objective is to explore the relationship between the dependent variable Log(C) and the independent variables Log(Q), Log(PF), and LF. Note that Log represents the Log function. To accomplish this, you may want to proceed as per the following steps:
a. Use Proc Corr to get the pairwise correlation coefficients between the variables.
b. Use Proc Plot to construct pairwise scatter plots to study the nature of the relationship between the dependent variable and the independent variables.
c. Use Proc Reg to run a multiple linear regression model.

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