Running head: DATA ANALYSIS 1

Data Analysis

Name

Institution

Date

DATA ANALYSIS 2

Results of the Data Analysis

Chi square analysis is used in the analysis of categorical variables. It actually tests the

independence between the variables. The null hypothesis is rejected when the p value is less than

or equal to the level of significance. Therefore on the basis of the study, the following is an SPSS

output of the chi square analysis between the job satisfaction and the gender.

Case Processing Summary

Cases

Valid

Missing

Total

DATA ANALYSIS 3

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * Gender of the

respondent

30

100.0%

0

0.0%

30

100.0%

How satisfied do you feel you are with your job? * Gender of the

respondent Cross tabulation

Count

Gender of the

respondent

Total

Male

Female

How satisfied do you

feel you are with your

job?

Highly satisfied

5

8

13

Slightly satisfied

3

0

3

Satisfied

6

5

11

Dissatisfied

1

0

1

Slightly

Dissatisfied

0

1

1

Highly

Dissatisfied

0

1

1

DATA ANALYSIS 4

Total

15

15

30

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

6.783

a

5

.237

Likelihood Ratio

9.107

5

.105

Linear-by-Linear

Association

.019

1

.891

N of Valid Cases

30

a. 8 cells (66.7%) have expected count less than 5. The

minimum expected count is .50.

The value of the asymptotic level of significance of the Pearson Chi square between the gender

and job satisfaction is 0.237.This value is greater than 0.05 and therefore the two variables are

dependent of each other.

The following is an SPSS output of the chi square analysis between the job satisfaction and the

age group.

Case Processing Summary

DATA ANALYSIS 5

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * Age of the

respondent

30

100.0%

0

0.0%

30

100.0%

How satisfied do you feel you are with your job? * Age of the respondent Crosstabulation

Count

Age of the respondent

Under 25

25-29

30-39

40-49

50-59

60+

How satisfied do you

feel you are with your

job?

Highly satisfied

1

1

4

5

1

1

Slightly satisfied

0

0

2

0

1

0

Satisfied

0

0

2

1

8

0

Dissatisfied

0

0

1

0

0

0

Slightly

Dissatisfied

0

0

0

0

1

0

Highly Dissatisfied

0

0

0

1

0

0

Total

1

1

9

7

11

1

DATA ANALYSIS 6

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

22.647

a

25

.598

Likelihood Ratio

24.492

25

.491

Linear-by-Linear

Association

2.675

1

.102

N of Valid Cases

30

a. 36 cells (100.0%) have expected count less than 5. The

minimum expected count is .03.

The p value of the Pearson chi square between the job satisfaction and the age group is

0.598.This value is greater than 0.05 and therefore the two categorical variables are dependent of

each other.

The following is an SPSS output of the Chisquare analysis of the job satisfaction and the status

of employment.

Case Processing Summary

DATA ANALYSIS 7

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * What is your

employment status as a

teacher?

30

100.0%

0

0.0%

30

100.0%

How satisfied do you feel you are with your job? * What is your employment status as a

teacher? Crosstabulation

Count

What is your employment status as a

teacher?

Total

Full time

Part time(less

than 50% of

the full time

hours)

Part time(50-

90% of the

full time

hours)

Highly satisfied

7

2

4

13

Slightly satisfied

2

1

0

3

DATA ANALYSIS 8

How satisfied do you

feel you are with your

job?

Satisfied

8

0

3

11

Dissatisfied

1

0

0

1

Slightly

Dissatisfied

0

0

1

1

Highly

Dissatisfied

1

0

0

1

Total

19

3

8

30

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

8.245

a

10

.605

Likelihood Ratio

10.027

10

.438

Linear-by-Linear

Association

.146

1

.703

N of Valid Cases

30

a. 16 cells (88.9%) have expected count less than 5. The

minimum expected count is .10.

The p value of the Pearson chi square between the job satisfaction and the employment status is

0.605.This value is greater than 0.05.Therefore, the two variables dependent on each other.

DATA ANALYSIS 9

The following is an SPSS output of the chi square analysis between the job satisfaction and the

time of service.

Case Processing Summary

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * How long have

you been in the

teaching profession?

30

100.0%

0

0.0%

30

100.0%

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

34.613

a

25

.095

Likelihood Ratio

24.173

25

.509

DATA ANALYSIS 10

Linear-by-Linear

Association

.005

1

.945

N of Valid Cases

30

a. 34 cells (94.4%) have expected count less than 5. The

minimum expected count is .03.

The p value of the Pearson chi square between the job satisfaction and the time of service is

0.095.This value is greater than 0.05.Therefore, the two variables dependent on each other.

The following is an SPSS output of the chi square analysis between the job satisfaction and the

basic pay.

Case Processing Summary

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * What is your

basic pay as an English

teacher?

30

100.0%

0

0.0%

30

100.0%

DATA ANALYSIS 11

How satisfied do you feel you are with your job? * What is your basic pay as an English

teacher? Crosstabulation

Count

What is your basic pay as an English

teacher?

Total

Less than

3000 yen per

hour

3000 yen per

hour

More than

3000 yen per

hour

How satisfied do you

feel you are with your

job?

Highly satisfied

3

1

9

13

Slightly satisfied

2

0

1

3

Satisfied

3

1

7

11

Dissatisfied

0

0

1

1

Slightly

Dissatisfied

0

0

1

1

Highly

Dissatisfied

1

0

0

1

Total

9

2

19

30

Chi-Square Tests

DATA ANALYSIS 12

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

5.886

a

10

.825

Likelihood Ratio

6.575

10

.765

Linear-by-Linear

Association

.254

1

.614

N of Valid Cases

30

a. 16 cells (88.9%) have expected count less than 5. The

minimum expected count is .07.

The p value of the Pearson chi square between the job satisfaction and the basic pay is

0.825.This value is greater than 0.05.Therefore, the two variables dependent on each other.

The following is an SPSS output of the chi square analysis between the job satisfaction and the

salary satisfaction.

Case Processing Summary

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

DATA ANALYSIS 13

How satisfied do you

feel you are with your

job? * How satisfied do

you feel you are with

your employment in

relation to your salary?

30

100.0%

0

0.0%

30

100.0%

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

19.053

a

25

.795

Likelihood Ratio

18.305

25

.829

Linear-by-Linear

Association

.231

1

.631

N of Valid Cases

30

a. 36 cells (100.0%) have expected count less than 5. The

minimum expected count is .03.

The p value of the Pearson chi square between the job satisfaction and the salary satisfaction is

0.795.This value is greater than 0.05.Therefore, the two variables dependent on each other.

DATA ANALYSIS 14

The following is an SPSS output of the chi square analysis between the job satisfaction and the

trajectory of the pay.

Case Processing Summary

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * How well can

you describe the

trajectory your pay has

taken in the past two

years?

30

100.0%

0

0.0%

30

100.0%

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

18.700

a

15

.228

DATA ANALYSIS 15

Likelihood Ratio

15.904

15

.388

Linear-by-Linear

Association

.920

1

.337

N of Valid Cases

30

a. 23 cells (95.8%) have expected count less than 5. The

minimum expected count is .03.

The p value of the Pearson chi square between the job satisfaction and the trajectory of the pay is

0.228.This value is greater than 0.05.Therefore, the two variables dependent on each other.

The following is an SPSS output of the chi square analysis between the job satisfaction and the

education level of teaching.

Case Processing Summary

Cases

Valid

Missing

Total

Sample

size

Percent

Sample

size

Percent

Sample

size

Percent

How satisfied do you

feel you are with your

job? * At what level in

the Japanese School

system do you teach?

30

100.0%

0

0.0%

30

100.0%

DATA ANALYSIS 16

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

14.876

a

20

.783

Likelihood Ratio

16.079

20

.712

Linear-by-Linear

Association

.384

1

.535

N of Valid Cases

30

a. 30 cells (100.0%) have expected count less than 5. The

minimum expected count is .03.

The p value of the Pearson chi square between the job satisfaction and the education level of

teaching is 0.783.This value is greater than 0.05.Therefore, the two variables dependent on each

other.

Testing of hypothesis

We wish to test hypothesis that the pay trajectory do not satisfy of the teachers. Since these are

two categorical variables, Chisquare analysis will be the most appropriate.

Therefore, the following is the SPSS output of the hypothesis.

DATA ANALYSIS 17

Chi-Square Tests

Value

Degrees

of

freedom

Asymp. Sig.

(2-sided)

Pearson Chi-Square

18.700

a

15

.228

Likelihood Ratio

15.904

15

.388

Linear-by-Linear

Association

.920

1

.337

N of Valid Cases

30

a. 23 cells (95.8%) have expected count less than 5. The

minimum expected count is .03.

The p value generated is 0.228 and therefore the hypothesis is rejected. Therefore, the pay

trajectory affects the satisfaction of the English teacher.

Summary of the findings

The analysis of the data indicates that the pay trajectory affects the job satisfaction of the teacher.

Obviously the pay of any worker needs to be reviewed as years go by so that their morale can be

boosted. The increase in the pay also indicate that the teachers have good experience from year

to year. Majority of the variables also indicate that they are dependent of the job satisfaction. The

analysis also indicate that the more the respondents age, the more the salary that the individual

receives. Consequently this means that such a respondent is satisfied with the job. The results

also indicate that the respondents who teach higher level of classes receive more than 3000 yen

DATA ANALYSIS 18

in the salary and this consequently mean that they are satisfied with the job. This study can be

extended to a larger sample so that the results can be confirmed. Since the study is concerned

with the pay and job satisfaction of the teachers in Japan, a large sample would give good results.

Probably a sample of 500 respondents could be considered for some confirmatory

analysis.However, the sample to be considered needs to be collected in a random manner. In a

random sample, all the respondents would have the same chances of being selected and therefore

bias will be avoided. Therefore, majority of the respondents indicated that there pay increased as

the time in the service increased. Some of them indicated that the pay was somehow reducing

given the workload. They felt that the workload was too much. Since the pay increased as

depending on the period of service and hence the pay trajectory, majority of the respondents

were satisfied with the job.

Reference

Levesque, R. (2005). SPSS programming and data management: A guide for SPSS and SAS

users. Spss.

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