Data analysis

Data analysis

Data 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

As it can be seen the first graph shows a negative skewed distribution. In negative skewed distribution the left tail is longer; the mass of the distribution is concentrated on the right of the figure. It has relatively few low values.

The second graph is right-skewed. In positive distribution, the right tail is longer; the mass of the distribution is concentrated on the left of the figure. It has relatively few high values.

The third graph is symmetric distribution. A skewed (non-symmetric) distribution is a distribution in which there is no such mirror-imaging.

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.

Comparison Krusal-Wallis test

Ranks

Sector

N

Mean Rank

Admin

manufacturing

30

46.03

private service sector

33

51.20

public sector

37

53.50

Total

100

Tutor

manufacturing

30

44.08

private service sector

33

49.21

public sector

37

56.85

Total

100

IT

manufacturing

30

68.48

private service sector

33

45.89

public sector

37

40.03

Total

100

You should use the output information in the following manner to answer the question.

Step 0 : Check Assumptions

The samples were taken randomly and independently of each other.

The populations have approximately the same shapes (according to the boxplots).

Step 1 : Hypotheses

H0: M1 = M2 = M3 (The median of three groups are equal.)

Ha: Not all of the medians are equal.

Step 2 : Significance Level

a = 0.05

Step 3 : Rejection Region

Reject the null hypothesis if p-value = 0.05.

Step 4 : Test Statistic

Test Statisticsa,b

Admin

Tutor

IT

Chi-Square

1.329

3.696

19.119

df

2

2

2

Asymp. Sig.

.514

.158

.000

a. Kruskal Wallis Test

b. Grouping Variable: Sector

Decision:

Since p value is 0< 0.05 we have to reject null hypothesis and conclude that mean between support services are equal.

Chi-Sq test between overall satisfaction levels in relation to support services satisfaction

Admin * Overall Crosstabulation

Count

Overall

Total

disagree

neutral

agree

strongly agree

Admin

disagree

1

1

0

0

2

neutral

7

13

2

0

22

agree

4

35

11

0

50

strongly agree

1

4

20

1

26

Total

13

53

33

1

100

Chi-Square ...