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Probabilities in the Business World - Essay Example

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Summary
This essay "Probabilities in the Business World" presents probabilities that are utilized in the business world to gauge the likelihood of an event occurring (Weiers, Gray & Peters, 2011). Probabilities are used in manufacturing companies to control the quality of products…
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Probabilities in the Business World
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Abstract

Male employees account for 44 percent while females account for 56 percent. Most of the employees are females while 12 employees have tenure of 2-5 years. The mean extrinsic job satisfaction of males is 5.32 while that of females is 5.42. 

Dear,  Head, American Intellectual Union (AIU)

            I am writing in regard to the level of job satisfaction in my organization. I have prepared statistics that will show you the employee demographic and work details and their level of job satisfaction. I hope this information will enable u to see the importance of proper job design, fair compensation, and job security to all employees.

Overview of the Data Set

            The Data Set provides information on the level of job satisfaction in the organization. It highlights how numerous employees attain their job satisfaction such as intrinsic, extrinsic, and benefit-linked job satisfaction. The Data set considers the demographic variables of all employees such as age and gender of the employee. Quantitative variables include the tenure with the company while qualitative variables include the department of work and compensation method.

Use of Statistics and Probability in the Real World

            The statistics are useful in the workplace in determining the compensation rates of employees. The statistics are also useful in job analysis and design and providing employee training. The statistics are also used by human resource managers in assessing the impact of employee benefits on the job satisfaction level of each employee. The statistics can be useful in analyzing the job performance of each employee and providing effective feedback. The statistics are useful in determining the job tenure of employees.

The Value of Statistics

            The statistics have a great value since they enable the human resource managers to design compensation packages that improve the level of job satisfaction and productivity of all employees. The statistics will enable the organization to reduce the rate of employee turnover and improve talent retention in the organization. The statistics will also help the organization reduce workplace accidents and possible go-slows that may adversely affect the reputation and production in organizations.

Distributions

            The distribution table provides information on the gender of each employee, the age group, department of work, tenure in the company, and their level of job satisfaction. The table also provides the job satisfaction survey measure of each employee which includes benefit-linked job satisfaction, intrinsic and extrinsic job satisfaction, and overall job satisfaction. AIU will utilize this information to design compensation packages that motivate employees.

Then complete the following distribution tables. 

Distribution of Individuals by Gender     

Gender

Percentage

Females

44

Males

56

 

Tenure with Company Distribution by Gender  

 

 

Under 2 years

2-5 Years

Over 5 years

Male

3

 

6

2

Female

7

 

6

1

 

Percentage of the Survey Participants in Each Department

           

Department

Percentage

Information Technology

64

Human Resources

28

Administration

8

 

 

Sample Mean for Extrinsic Value by Gender

Gender

Mean Extrinsic Value

Male

5.32

Female

5.41

 

Probabilities

            Below are the probabilities of an individual being aged between 16-21 years, the probability that an individual’s overall job satisfaction is 5.2 or lower, the probability of a female being in the human resource department, and the probability that a salaried employee will have an intrinsic motivation of 5 or more.

They are also used in investment appraisals in determining the risks and expected return of investment portfolios (Weiers, Gray & Peters, 2011).

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