# Modelling of Engineering Management Systems

ENGG953: Modelling of Engineering Management Systems

Assignment 2

Submitted Date:December 8, 2017

Due Date: December 28,2017

Submission Form: Hard copy Binded includes (bind the two reviewed research journal articles with the full report)

Part A.

Problem 1

Review one research articles in the area of engineering that includes regression analysis. The research should have been carried out by the author(s). The article must be directed at a scholarly audience. State clearly the research question, the author interest, state clearly the hypothesis intended to be tested by regression. Describe the dependent variable and the independent variables. You need to discuss the type of data and its source (give a brief overview of how the data was acquired, collected, observed or measured).

Discuss the findings, the tests of the assumptions. Give interpretation of the results anddiscuss the author conclusion in relation of the regression findings. In case you have access to the research data, carry out the checking of the assumptions. The scientific article should have been published in ranked journals A or B.

Problem 2

Sameas in Problem 1 where the article employs the Analysis of Variance.

Length: Two to three pages typed for each article.

Source of the Journal article:Use the data bases available through the Library home page. UOWD subscribes to a large number of electronic form journals. Provide the research articles with the report.So you need to spot two articles that look interesting to you in terms of the use.

1) First Article : Regression analysis.25%

2) Second Article: Analysis of variance (one way ANOVA or Two Factor ANOVA or One factor Anova with blocking or repeated Anova) 25%

Group work:

All the members are expected to contribute to the writing of the report. All the members are responsible for any plagiarism. The groups are expected to work independently. You should submit your work as a report in a binding form.

Note: (Do not search through web).

The marking criteria will be based on

· Selection of the article which describes the statistical approach (regression) with enough detail to enable you to have a knowledgeable awareness of the research conducted and possible access to the original data to verify the reported results ( if possible).

· Describe the use of statistical versus the research hypothesis.

· The effort made by the team in understanding the article and the regression employed in the analysis (Do not give a summary of the paper).

· The report should demonstrate that you have (s) grasped the important concepts

· The report should demonstrate some relevant evidence of depth understanding of the objective of the empirical research conducted by the author(s)

· The quality of the writing (do not rewrite the research article). The report should be coherent

· The completeness and validity of the material in relation to the Author(s) research question

· The validity of the tested hypothesis in relation to the Author(s) research question

· Explicit awareness of strength and weakness of the research

· The quality of presentation and organization of the report, including the quality of expression

· Detail the empirical method

· Apply the critiquing criteria to the evaluation of the paper and its hypothesis

· Evaluate the method and the instrument used in the empirical analysis and state limitation(s)

Par B 20%

Problem 1 Regression

Data for this Problem is found below (you may copy and paste to SPSS or to Excel)

The data contains:

Y: beginning salary in $

X1: Years of schooling (Educ)

X2: number of months of previous work

X3: number of months after January 1, 1989 that the individual was hired

X4: indicator variable coded 1 for males and 0(females)

X5: indicator variable coded 0 for males and 1(males)

a) Conduct your regression of salary on the explanatory variables.Which variables are significant (explain) (use α=0.05)?

b) Interpret the overall model (Test the validity of the overall model)

c) Interpret the fourth variableresults (X4)

d) conduct the hypothesis at (α=0.05) of (educ=0 and establish the 90% confidence interval for the marginal slope of Educ (X1)

e) Is there a significant difference in salaries, on average for male and female workers before controlling for the other three explanatory variables?

f) Assess the normality assumption of the full model

g) Check your model for multi-collinearity

h) What would happen if you include both X4 and X5 into the model (what do you call such a case in regression)?

Data for Problem 1

Y

X1

X2

X3

X4

X5

Observation

SALARY

EDUCAT

EXPER

MONTHS

MALES

females

1

3900

12

0

1

0

1

2

4020

10

44

7

0

1

3

4290

12

5

30

0

1

4

4380

8

6

7

0

1

5

4380

8

8

6

0

1

6

4380

12

0

7

0

1

7

4380

12

0

10

0

1

8

4380

12

5

6

0

1

9

4440

15

75

2

0

1

10

4500

8

52

3

0

1

11

4500

12

8

19

0

1

12

4620

12

52

3

0

1

13

4800

8

70

20

0

1

14

4800

12

6

23

0

1

15

4800

12

11

12

0

1

16

4800

12

11

17

0

1

17

4800

12

63

22

0

1

18

4800

12

144

24

0

1

19

4800

12

163

12

0

1

20

4800

12

228

26

0

1

21

4800

12

381

1

0

1

22

4800

16

214

15

0

1

23

4980

8

318

25

0

1

24

5100

8

96

33

0

1

25

5100

12

36

15

0

1

26

5100

12

59

14

0

1

27

5100

15

115

1

0

1

28

5100

15

165

4

0

1

29

5100

16

123

12

0

1

30

5160

12

18

12

0

1

31

5220

8

102

29

0

1

32

5220

12

127

29

0

1

33

5280

8

90

11

0

1

34

5280

8

190

1

0

1

35

5280

12

107

11

0

1

36

5400

8

173

34

0

1

37

5400

8

228

33

0

1

38

5400

12

26

11

0

1

39

5400

12

36

33

0

1

40

5400

12

38

22

0

1

41

5400

12

82

29

0

1

42

5400

12

169

27

0

1

43

5400

12

244

1

0

1

44

5400

15

24

13

0

1

45

5400

15

49

27

0

1

46

5400

15

51

21

0

1

47

5400

15

122

33

0

1

48

5520

12

97

17

0

1

49

5520

12

196

32

0

1

50

5580

12

133

30

0

1

51

5640

12

55

9

0

1

52

5700

12

90

23

0

1

53

5700

12

117

25

0

1

54

5700

15

51

17

0

1

55

5700

15

61

11

0

1

56

5700

15

241

34

0

1

57

6000

12

121

30

0

1

58

6000

15

79

13

0

1

59

6120

12

209

21

0

1

60

6300

12

87

33

0

1

61

6300

15

231

15

0

1

62

4620

12

12

22

1

0

63

5040

15

14

3

1

0

64

5100

12

180

15

1

0

65

5100

12

315

2

1

0

66

5220

12

29

14

1

0

67

5400

12

7

21

1

0

68

5400

12

38

11

1

0

69

5400

12

113

3

1

0

70

6000

15

25

13

1

0

71

6000

15

36

32

1

0

72

6000

15

56

12

1

0

73

6000

15

64

33

1

0

74

6000

15

108

16

1

0

75

6000

16

46

3

1

0

76

6300

15

72

17

1

0

77

6600

15

64

16

1

0

78

6600

15

84

33

1

0

79

6600

15

216

16

1

0

80

6840

15

42

7

1

0

81

6900

12

175

10

1

0

82

6900

15

132

24

1

0

83

8100

16

55

33

1

0

Problem 2 15%

Ten students performed four recall tasks. The Experiment results are given below:

image1.png

a. Conduct the analysis to test whether all population means of the four tests are equal. Discuss the test of assumptions. Explain the partitioning of the total variance.

b. Suppose the first 6 subjects are male and the other 4 subjects are female. Suggest appropriate hypotheses and test them.

Problem 3 15%

Based on the following data:

Response Factor A Factor B

image2.emf

ResponseFactor AFactor B

810

11

820

11

820

11

840

21

840

21

845

21

785

31

790

31

785

31

835

11

835

11

835

11

845

21

855

21

850

21

760

31

760

31

770

31

820

12

820

12

820

12

820

22

820

22

825

22

775

32

775

32

775

32

825

12

825

12

825

12

815

22

825

22

825

22

770

32

760

32

765

32

1) Conduct one way one Anova on Factor A and interpret the results. conduct a post-hoc test if needed.

2) Conduct Two_way_Anova (two way anova with repelication) on the two factors, interpret the results and include interaction graphs.

3) Conduct a two-way analysis of variance using blocking where the blocking factor is A and the main factor isB. Interpret the results and compare corresponding variance between the various techniques.

4) Test ANOVA assumptions

1