Discussion Analysis on Employee Satisfaction

The owner of the organization is trying to improve employee relations. The goal of the owner is to increase employee satisfaction up to 75%. The chi-square test is utilized to predict the owner’s expectations. The following are the hypothesis:

H₀: Employees of the organization are satisfied

H₁: Employees of the organization are not satisfied

Level of Significance

Statistic Test  of Employee

The Formula for evaluating the statistic test value is mentioned as follows:

In the first step, the predicted values are going to be calculated so that they can be compared with actual values of survey. According to the available data the predicted number of employees that are satisfied is 75%. It means that the remaining 25% number of employees in each department are dissatisfied. Now the predicted number of satisfied employees in the finance department is evaluated as 0.75(19) = 14.25. Similarly the predicted number of dissatisfied employees in the finance department is 0.25(19) = 4.75 (Wegner, 2010). In the below table the details regarding the expected and observed values are presented:

The expected & observed values are utilized for evaluating the Chi-Square:

Part B of Employee Satisfaction:

After calculating the Chi-square the next step is to find the p-value. The Chi-square table can be utilized for finding the p-value. As there are 4 departments in the organization the degree of freedom (df) would be 3. In the chi-square table, the row of degree of freedom 3, the nearest value to 5.124 will be selected. The nearest value to 5.124 is 6.251 which indicates the p-value of 0.10. The level of significance of 0.05 is used to determine whether to accept or reject the hypothesis. As the p-value of 0.10 > 0.05 the H₀ will not be rejected which means that employees are satisfied with the organization (Anderson, Sweeney, & Williams, 2010).

Part C of Employee Satisfaction:

The study conducted by Mary L. McHugh (2013) has provided brief overview regarding Chi-square and how Chi-square can be used for evaluating the group differences. The researcher has stated that the chi-square has many benefits such as easy calculations and its robustness in data distribution. However, Chi-square has some drawbacks as well which include difficulty in interpretation and sample size requirements. The chi-square can be utilized in different business scenarios such as knowing the motivational level of the employees and how efficiently each employee’s performance in the organization (McHugh, 2013).

References of Employee Satisfaction

Anderson, Sweeney, D. J., & Williams, T. A. (2010). Fundamentals of Business Statistics (illustrated ed.). Cengage Learning.

McHugh, M. L. (2013). The Chi-square test of independence. Biochemia Medica, 23(2), 143-149.

Wegner, T. (2010). Applied Business Statistics: Methods and Excel-based Applications (illustrated ed.). Juta and Company Ltd.