SLP/BUS520 Business Analytics And Decision Making Business Analytics & Intelligence Reporting Final Analysis **Complete Module 4 SLP before Module 4 Case** We have been working with survey data

BUS520 SLP 2

Trident University International

BUS 520 Business Analytics and Decision Making

May 26, 2024

The hypothesis testing process is essential since numerical data is analyzed to determine whether the research question is accepted or rejected. This paper will involve running data, such as job and intrinsic and extrinsic satisfaction against the gender variables.

The t-test of job satisfaction

(Table 1: t-test of job satisfaction)

Since the p values of the data are critically low, the null hypothesis is rejected when the t-statistics are higher than the critical values. The analysis above means that there is a significant difference between job satisfaction and gender. Therefore, there is a difference between the satisfaction of men and women in the industry. The t-test of 28.6 is relatively higher, which means that there is a high difference between the two variable (Kim, 2015). While the one-tail and p-value are small. However, the data shows that the males are more satisfied with the job than the females, an essential factor that should be considered during employee motivation programs within the organization.

The t-test of intrinsic job satisfaction

(Table 2: t-test of intrinsic job satisfaction)

Since the p-value of 2.83 E-p3 is significantly less than the alpha of 0.05, we will reject the null hypothesis. This means that the alternative hypothesis is accepted which is that males have higher intrinsic satisfaction then females. This means that the industry is male-dominated, and the females feel negatively pressured from joining. Since the t-test value is very high, there is a big difference between the male and female groups. The p-values and t-statistics exceed the critical values by far, meaning the null hypothesis is rejected.

T-test of extrinsic satisfaction

(Table 3: T-test of extrinsic satisfaction)

In this case, the null hypothesis is rejected since the p-value (1.91E-123) is relatively lower than the alpha of 0.05. This supports the alternative hypothesis that the male's satisfaction is different from the females within the organization. (De Winter, 2019). The extrinsic satisfaction occurs when employees are satisfied while working for a specific firm. Women may not be well-valued or rewarded in the industry, which significantly lowers their satisfaction. Additionally, there may be no appropriate feedback systems to allow women to express themselves. The best way to solve this problem is to develop employee-centric communication systems to ensure everyone’s opinions are respected.

T-test of organizational commitment

(Table 4: T-test of organizational commitment)

Since the p-value is relatively lower than the alpha of 0.05, the null hypothesis of rejected in this case. Meaning that the organizational commitment of men is diferent than the females in the organization. (Mishra et al., 2019). The organization's commitment is caused by workers value and connection with their organization forcing them to keep working productively. The females provided a relatively lower score than the men in this case. This could be interpreted as women having a lower bond with the organization than men. The organization could embrace communication and reward systems to ensure women feel valued, thus boosting commitment.

Conclusion

Through statistical analysis, it is possible to comprehensively analyze different industries and understand relations between complex data. Based on the information analyzed, men's satisfaction is different from that of women. In all categories, the null hypothesis was rejected.

References

De Winter, J. C. (2019). Using the Student's t-test with extremely small sample sizes. Practical Assessment, Research, and Evaluation, 18(1), 10.

Kim, T. K. (2015). T test as a parametric statistic. Korean Journal of Anesthesiology, 68(6), 540.

Mishra, P., Singh, U., Pandey, C. M., Mishra, P., & Pandey, G. (2019). Application of Student's t-test, analysis of variance, and covariance. Annals of cardiac anesthesia, 22(4), 407-411.