Suppose another researcher gathered survey data from 19 employees on these questions and also asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represents the results of this survey. Assume that the relationship with the supervisor is rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent relationship), the overall quality of the work environment is rated on a scale from 0 to 100 (0 represents a poor work environment and 100 represents an excellent work environment), and opportunities for advancement are rated on a scale from 0 to 50 (0 represents no opportunities and 50 represents excellent opportunities).
JOB SATISFACTION
RELATIONSHIP WITH SUPERVISOR
OVERALL QUALITY OF WORK ENVIRONMENT
TOTAL HOURS WORKED PER WEEK
OPPORTUNITIES FOR ADVANCEMENT
55
27
65
50
42
20
12
13
60
28
85
40
79
45
7
65
35
53
65
48
45
29
43
40
32
70
42
62
50
41
35
22
18
75
18
60
34
75
40
32
95
50
84
45
48
65
33
68
60
11
85
40
72
55
33
10
5
10
50
21
75
37
64
45
42
80
42
82
40
46
50
31
46
60
48
90
47
95
55
30
75
36
82
70
39
45
20
42
40
22
65
32
73
55
12
Managerial and Statistical Questions
1. Several variables are presented that may be related to job satisfaction. Which variables are stronger predictors of job satisfaction? Might other variables not mentioned here be related to job satisfaction?
2. What variables might be used? What variables should not be used? To what degree can someone depend on the results of the regression analysis? Why?
3. Is it possible to develop a mathematical model to predict job satisfaction using the given data? If so, how strong is the model? With four independent variables, will we need to develop four different simple regression models and compare their results?