Predicting linear regression equation

Reference no: EM1315511

Delta Wire prides itself on its efforts in the area of employee education. Employee education can pay off in many ways. Discuss some of them. One payoff can be the renewed interest and excitement generated toward the job and the company. Some people theorize that because of a more positive outlook and interest in implementing things learned, the more education received by a worker, the less likely he or she is to miss work days. Suppose the following data represent the number of sick leave taken by 20 workers last year along with the number of contact hours of employee education/training they each received in the past year. Use the techniques learned in this chapter to analyze the data. Include both regression and correlation techniques. Discuss the strength of the relationship and any models that are developed.

EMPLOYEE	HOURS OF EDUCATION	SICK DAYS
1	24	5
2	16	4
3	48	0
4	120	1
5	36	5
6	10	7
7	65	0
8	36	3
9	0	12
10	12	8
11	8	8
12	1	1
13	9	9
14	3	3
15	8	8
16	2	2
17	1	1
18	8	8
19	0	0
20	10	10

Attach excel or Minitab output (the output you generated using data set given in the question). Then by using output answer the following questions.

(a) Write the linear equation. How would you explain slope in this case.

(b) Develop a scatter diagram using excel or Minitab. What is the value of multiple R?

(d) Is this model statistically significant? Conduct hypothesis test. Use α = 0.05

(e) Draw a normal probability plot for residuals using excel or Minitab. Do the residuals seem normally distributed? If yes, why?

(f) Would you recommend using this model? Explain why or why not.

Reference no: EM1315511

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