Question

How do I use the data analysis in Excel to figure these questions out?

Suppose a researcher gathered survey data from 19 employees and asked the employees to rate their job satisfaction on a scale from 0 to 100 (with 100 being perfectly satisfied). Suppose the following data represent the results of this survey. Assume that relationship with their supervisor is rated on a scale from 0 to 50 (0 represents a poor relationship and 50 represents an excellent relationship); overall quality of the work environment is rated on a scale from 0 to 100 (0 represents poor work environment and 100 represents an excellent work environment); and opportunities for advancement is rated on a scale from 0 to 100 (0 represents no opportunities and 100 represents excellent opportunities).

Answer the following questions:

1. What is the regression formula based on the results from your regression?
2. How reliable do you think the estimates will be based on this formula? Explain your answer by citing the relevant metrics.
3. Are there any variables that do not appear to be good predictors of job satisfaction? How can you tell?
4. If a new employee reports that her relationship with her supervisor is 40, rates her opportunities for advancement to be at 30, finds the quality of the work environment to be at 75, and works 60 hours per week, what would you expect her job satisfaction score to be?

Job satisfaction	Relationship with supervisor	Opportunities for advancement	Overall quality of work environment	Total hours worked per week
55	27	42	50	52
20	35	28	60	60
85	40	7	45	42
65	35	48	65	53
45	29	32	40	58
70	42	41	50	48
35	22	18	75	55
60	34	32	40	50
95	40	48	45	40
65	33	11	60	38
85	38	33	55	47
10	5	21	50	62
75	37	42	45	43
80	37	46	40	42
50	31	48	60	46
90	42	30	55	38
75	36	39	70	43
45	20	22	40	42
65	32	12	55	53

Answer 1

Enter the data into Excel.

Now, go to Data > Data Analysis > Regression.

Select the input range and click OK. Check Labels too.

The output is:

1. What is the regression formula based on the results from your regression?

y = 98.32909 + 1.323244*x1 + 0.077349*x2 - 0.17004*x3 - 1.52239*x4

1. How reliable do you think the estimates will be based on this formula? Explain your answer by citing the relevant metrics.

R-square = 0.82

Since 82% of the variation in the model is explained, we can say that the estimates are reliable.

1. Are there any variables that do not appear to be good predictors of job satisfaction? How can you tell?

Opportunities for advancement is not a good predictor of job satisfaction.(p > .05)

Overall quality of work environment is not a good predictor of job satisfaction.(p > .05)

1. If a new employee reports that her relationship with her supervisor is 40, rates her opportunities for advancement to be at 30, finds the quality of the work environment to be at 75, and works 60 hours per week, what would you expect her job satisfaction score to be?

y = 98.32909 + 1.323244*40 + 0.077349*30 - 0.17004*75 - 1.52239*60 = 49.48292

Please give me a thumbs-up if this helps you out. Thank you!