Business Research Analysis

Business Research Analysis

Data

A data set consisting of 100 student records from the flexible delivery MBA programme. The data consists of 100 student records and the following variables:

The student ID number, recorded as 1 to 100 inclusive.

The satisfaction scores relating to administrative, tutor and IT support, labelled as Admin, Tutor and IT respectively. These are scored 1 to 5 inclusive, where 1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree and 5 = strongly agree

An assessment of Overall satisfaction, scored as above.

The final average mark obtained by the student on their MBA programme.

The number of hours of private study undertaken by the student.

The number of additional seminars attended, which are provided on a weekend basis to the distance-learning students.

Student gender, where 1 = male and 2 = female.

The sector in which the student is employed, where 1 = manufacturing, 2 = private service sector and 3 = public sector.

If the student would recommend the University and programme to others, where 0 = no, 1 = yes.

Demography of the Data

Gender

Frequency

Percent

Valid Percent

Cumulative Percent

Valid

Male

40

40.0

40.0

40.0

Female

60

60.0

60.0

100.0

Total

100

100.0

100.0

From above pie chart we can observe that major part of our data is consists of females, there is a ratio is 60:40.

Cross Tabulation of Sector and IT

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

Sector * IT

100

100.0%

0

.0%

100

100.0%

Sector * IT Crosstabulation

Count

IT

Total

SD

D

N

A

SA

Sector

manufacturing

0

4

10

11

5

30

private service sector

1

14

11

5

2

33

public sector

2

15

18

2

0

37

Total

3

33

39

18

7

100

We can observe that a little bit large amount of data is from Public sector but there is not large difference among the three sectors. In IT most of the respondents were neutral and disagree.

Cross Tabulation of Sector and Tutor

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

Sector * Tutor

100

100.0%

0

.0%

100

100.0%

Sector * Tutor Crosstabulation

Count

Tutor

Total

SD

D

N

A

SA

Sector

manufacturing

3

7

13

7

0

30

private service sector

0

11

12

7

3

33

= public sector

0

6

17

12

2

37

Total

3

24

42

26

5

100

We can observe that a little bit large amount of data is from Public sector but there is not large difference among the three sectors. In Tutor most of the respondents were neutral, agree and disagree.

Cross Tabulation of Sector and Admin

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

Sector * Admin

100

100.0%

0

.0%

100

100.0%

Sector * Admin Crosstabulation

Count

Admin

Total

D

N

A

SA

Sector

manufacturing

1

10

11

8

30

private service sector

0

9

14

10

33

= public sector

1

3

25

8

37

Total

2

22

50

26

100

We can observe that a little bit large amount of data is from Public sector but there is not large difference among the three sectors. In Admin most of the respondents were agree.

Chi-square test

The chi-square is one of the most popular statistics because it is easy to calculate and interpret. There are two kinds of chi-square tests. The first is called a one-way analysis, and the second is called a two-way analysis. The purpose of both is to determine whether the observed frequencies (counts) markedly differ from the frequencies that we would expect by chance.

Chi Square Test of Seminar and Hours

Case Processing Summary

Cases

Valid

Missing

Total

N

Percent

N

Percent

N

Percent

Hour * Seminar

100

100.0%

0

.0%

100

100.0%

Hour * Seminar Crosstabulation

Count

Seminar

Total

0

1

2

3

Hour

75

1

1

0

0

2

80

0

0

0

1

1

90

0

0

0

1

1

100

3

9

2

0

14

120

0

1

1

0

2

125

4

9

8

2

23

140

0

0

1

0

1

150

9

10

6

2

27

160

0

1

1

0

2

175

5

2

4

0

11

180

0

2

0

0

2

200

0

5

3

2

10

225

1

0

1

0

2

250

0

1

1

0

2

Total

23

41

28

8

100

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

50.437a

39

.104

Likelihood Ratio

44.534

39

.250

Linear-by-Linear Association

.206

1

.650

N of Valid Cases

100

a. 49 cells (87.5%) have expected count less than 5. The minimum expected count is .08.

From Chi square test we observed that there is a strong relationship among seminars and Hours. Max no. of Seminars: Those who study 150 hours attend only 1 seminar, those who study 125 hours attend 2 seminars and those who study 125, 150 and 200 hours attend 3 seminars. While in entire sample students who ...