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The main challenge in the business is deterioration in job satisfaction among the employees. For this reason the company HR has decided to conduct a survey and identify satisfaction level of the employees. They measure employees satisfaction in two periods of before and after training.

Using statistical theory and application to answer the main research questions below. Also consider the dataset and answer any other research questions that are meaningful to you.

As guide - answer these main research questions. They should be analysed and illustrated through graph or chart or table or a combination:

1.What is the frequency of each of the variables? E.g. married vs unmarried.

2.Are there any meaningful differences between the job satisfaction score before and after training?

3.Are there any differences in the gender on job satisfaction? Both for satisfaction before and after training.

4.Are there any differences in gender on age?

5.What measures of location/variables you can use to present the data?

6.What measures of variation/variables you can use to present the data?

• Introduction– Introduce the business and its problems.
• Describe the company, what does it do
• Problem definition and business intelligence required
• Defining problem of the business and what they are trying to achieve by the analysis
• If you used any measures (e.g. measures of variation) explain why it was most appropriate by defining what that particular measure is and what it does
• Identifying the data variables as data types and measurement scales
• Are the variables in the data Numerical, nominal/categorical, or ordinal. What are the scales of measurements?

## Problem definition

In order to set this research work straight, it is only in order to understand the meaning of job satisfaction. According to this research paper, job satisfaction is that feeling of fulfillment that employee gets as a result of doing their job (Barton , 2001). Job satisfaction is a key factor in any organization as it determines the productivity of the organization (Verson , 2016)and ( Pierce , 2004). This is because a satisfied employee will have a high morale of doing work hence improving productivity. However, a dissatisfied employee will have a low morale towards work hence lowering productivity at work (Lin , 2010). So in order to boost the morale and hence their job satisfaction, employers are encouraged to create a good working environment, have fair promotion systems and cultivate good leadership behavior.  XYZ Company has had a difficult year. There have been low sales due to low production (Sousa-Poza , 2000) and (Zhao , 2009). It is perceived that this situation has been occasioned by low morale due to dissatisfaction of the employees. It is against this background that XYZ Company has decided to carry out a research on their employees focusing on their satisfaction.

XYZ Company has had a difficult year. There have been low sales due to low production. It is perceived that this situation has been occasioned by low morale due to dissatisfaction of the employees. It is against this background that XYZ Company has decided to carry out a research on their employees focusing on their satisfaction. The research has employed statistical analysis in order to turn the data into information that can be acted upon. Descriptive statistics was used to establish the mean satisfaction level.

Data variable and types

This research involved both numerical and non-numerical variables. The numerical variables were age, years of experience and salary. The dichotomous categorical variables were gender and marital status. Other categorical variables were job satisfaction before and after training, life happiness score and promotion.

Descriptive statistics

 Statistics age in years Years of experience salary amount in 1000s N Valid 300 300 300 Missing 0 0 0 Mean 41.8800 20.7067 47.3600 Median 42.0000 23.0000 47.0000 Mode 54.00 25.00a 45.00 Std. Deviation 10.17895 9.53785 6.67775 Variance 103.611 90.971 44.592 Minimum 20.00 1.00 26.00 Maximum 60.00 36.00 65.00 Interquartile range 1st quartile 32.0000 13.0000 44.0000 2nd quartile 42.0000 23.0000 47.0000 3rd quartile 50.0000 28.0000 52.0000 a. Multiple modes exist. The smallest value is shown

Table 1

The above table shows the descriptive statistics for age of employees, years of experience and salary amount. It can be observed that the mean age of the employees was 41.9 years. The median age was 42 years. The youngest employee was 20 years old while the oldest employee was 60 years old. The ages deviated from the mean by 10.17 years.  It can also be observed that the mean years of experience of employees were 20.7 years. The median years of experience of employees were 23 years. The years of experience of employees deviated from the mean by 9.5 years.  When it comes to salary, it can be seen that the mean salary of the employees at XYZ was 47,360. The median salary was 47,000. The least earning employee got 26,000 while the highest earning employee was 65,000. The salary of experience of employees deviated from the mean by 6.677.

METHODS OF DATA SUMMARIZING

Summary of gender distribution

 male or female Frequency Percent Valid Percent Cumulative Percent Valid Male 114 38.0 38.0 38.0 Female 186 62.0 62.0 100.0 Total 300 100.0 100.0

Table 2

Table 2 and figure 1 above illustrates the distribution of XYZ Company employees by gender. As can be observed, the males were 114 while the females were 186.

## Data variable and types

Marital status distribution

 married or not married Frequency Percent Valid Percent Cumulative Percent Valid Married 252 84.0 84.0 84.0 Single 48 16.0 16.0 100.0 Total 300 100.0 100.0

Table 3

Table 3 and figure 2 above illustrates the distribution of XYZ Company employees by their marital status. As can be observed, the married employees were 252 while the single employees were 48.

Distribution of employees by place of origin

 Region of origin Frequency Percent Valid Percent Cumulative Percent Valid East 71 23.7 23.7 23.7 North 47 15.7 15.7 39.3 South 59 19.7 19.7 59.0 West 123 41.0 41.0 100.0 Total 300 100.0 100.0

Table 4 and figure 3 above illustrates the distribution of XYZ Company employees by their places of origin. As can be observed, the employees from east were 71, the employees from north were 47, the employees from south 59 and the employees from west were 123.

 working department Frequency Percent Valid Percent Cumulative Percent Valid IT 101 33.7 33.7 33.7 Marketing 109 36.3 36.3 70.0 Sales 32 10.7 10.7 80.7 Human resource 30 10.0 10.0 90.7 Finance 15 5.0 5.0 95.7 Innovation 13 4.3 4.3 100.0 Total 300 100.0 100.0

Table 5

Table 5 and figure 3 above illustrates the distribution of XYZ Company employees by the departments they work in. As can be observed, the employees who worked in the IT department were 101. Those who worked in the marketing department were 109 while those who worked in the sales department were 32. In the human resource department, there were 30 employees. The finance department had 15 employees while the innovation department had 13 employees.

Distribution of employees according to whether they have had promotion

 have been promoted Frequency Percent Valid Percent Cumulative Percent Valid No 110 36.7 36.7 36.7 Yes 190 63.3 63.3 100.0 Total 300 100.0 100.0

Table 6

Table 6 and figure 5 above illustrate the distribution of XYZ Company employees according to whether they have had promotion or not. As can be observed, the employees who have had promotion were 190 while those who have had no promotion were 110.

Inferential statistics

Hypothesis 1

H0: There is no difference between the job satisfaction score before and after training

Versus

H1: There is a significant difference between the job satisfaction score before and after training

A paired sample t-test was employed to establish whether there was a significant difference in job satisfaction before training and after training.

Table of results

 Paired Samples Test Paired Differences t df Sig. (2-tailed) Mean Std. Deviation Std. Error Mean 95% Confidence Interval of the Difference Lower Upper Pair 1 Job satisfaction score before training - Job satisfaction score after training -1.44333 1.48576 .08578 -1.61214 -1.27452 -16.826 299 .000

Table 7

From the t-test results above, it can be seen that the p-value computed is 0.00. This value is less than the value of level of significance which is 0.05. The decision rule is to reject the null hypothesis and accept the alternative. It is concluded that there is a significant difference between the job satisfaction score before and after training.

Hypothesis 2

H0: There is no difference in job satisfaction score before training between males and females.

Versus

H1: There is a significant difference in job satisfaction score before training between males and females.

A paired sample t-test was employed to establish whether there was a significant difference in job satisfaction score before training between males and females.

Table of results

 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Job satisfaction score before training Equal variances assumed 1.055 .305 1.321 298 .187 .14997 .11352 -.07342 .37337 Equal variances not assumed 1.300 226.603 .195 .14997 .11539 -.07740 .37735

Table 8

From the t-test results above, it can be seen that the p-value computed is 0.18. This value is greater than the value of level of significance which is 0.05. The decision rule is to accept the null hypothesis and reject the alternative. It is concluded that there is a significant difference in job satisfaction score before training between males and females.

Hypothesis 3

H0: There is no difference in job satisfaction score after training between males and females.

Versus

H1: There is a significant difference in job satisfaction score after training between males and females.

A paired sample t-test was employed to establish whether there was a significant difference in job satisfaction score before training between males and females.

Table of results

 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper Job satisfaction score after training Equal variances assumed .024 .876 -.762 298 .447 -.09819 .12886 -.35178 .15541 Equal variances not assumed -.753 230.429 .452 -.09819 .13033 -.35498 .15860

Table 9

From the t-test results above, it can be seen that the p-value computed is 0.88. This value is greater than the value of level of significance which is 0.05. The decision rule is to accept the null hypothesis and reject the alternative. It is concluded that there is a significant difference in job satisfaction score after training between males and females.

Hypothesis 4

H0: There is no difference in age between males and females.

Versus

H1: There is a significant difference in age between males and females.

A paired sample t-test was employed to establish whether there was a significant difference in job satisfaction score before training between males and females.

 Independent Samples Test Levene's Test for Equality of Variances t-test for Equality of Means F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% Confidence Interval of the Difference Lower Upper age in years Equal variances assumed 2.464 .118 4.224 298 .000 4.97566 1.17803 2.65735 7.29398 Equal variances not assumed 4.091 215.029 .000 4.97566 1.21629 2.57829 7.37304

Table 10

From the t-test results above, it can be seen that the p-value computed is 0.00. This value is less than the value of level of significance which is 0.05. The decision rule is to reject the null hypothesis and accept the alternative. It is concluded that there is a significant difference in there is a significant difference in age between males and females.

Discussion of the results

From the analyses above, several recommendations and conclusions could be made. Majority of the employees in XYZ were married. 252 out of 300 were married while the rest were single. To add on, majority of the employees were females. Out of 300 employees, they were 186. The department which had the largest number of employees was the marketing department which had 109 employees out of 300. The innovation department had the least number of employees. Inferential statistics has found that there was significant difference in the mean satisfaction level between the males and the females. This means that one group was more satisfied than the other when it came to job satisfaction. This research therefore recommended further research to find out the reason for the difference in satisfaction levels. It was also found that there is a significant difference between the job satisfaction score before and after training. The research supposes that there was a great improvement in satisfaction after training.

References

Pierce , L. (2004). The effects of pay level on organization based self-esteem and performance.

Barton , M. (2001). The impact of job satisfaction on turnover intent: a test of structural measurement model using a national sample of workers.

Lin , C. (2010). Employee empowerment in a technology advanced work environment.

Sousa-Poza , A. (2000). Well-being at work. A cross-national analysis of the levels and determinants of job satisfaction.

Verson , R. (2016). Employee acceptance of organizational change. The role of organizational commitment.

Zhao , J. (2009). The determinants of job satisfaction among United States Air Force’s security police

Cite This Work

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