Project 2 - Dataset E Nicholas Amoroso

STUDENT NAME: OBJECTIVES: The project introduces you to the methods of organizing, summ data using tools available in MS Excel. You will apply various ta inferential techniques to describe and transform raw data into test hypotheses, make estimates, validate statistical claims and problems. GRADE: Data Analysis Project 2 - Dataset E

marizing, analyzing and interpreting abular, graphical, descriptive and meaningful information as well as to d assumptions relating to everyday

Employee ID Age Job Rank 172 32 Front-Line Maintenance Rarely 560.95 178 31 Supervisor Administration Never 800.24 489 32 Manager Maintenance Rarely 1200.19 622 44 Manager Production Sometimes 890.00 568 43 Manager Production Often 1450.45 890 47 Front-Line Logistics Often 600.00 900 44 Front-Line Maintenance Often 750.79 339 67 Front-Line Production Sometimes 780.00 408 41 Front-Line Maintenance Never 600.48 309 59 Front-Line Production Rarely 440.00 588 63 Front-Line Production Sometimes 400.00 149 40 Front-Line Production Sometimes 700.05 Variable Description Employee ID A unique identification number assigned to the employee Age The age of the employee (in years) Job Rank The rank position of the employee (frontline, supervisor or manage Work Department The deparment the employee works at (production, maintenance, a Frequency of Overtime How often the employee has worked overtime (never, rare, sometim Weekly Income The income earned by the employee in a given week (in $). Likely To Change Job The likelihood of the employee changing job within the next 3-5 yea No of Job Error The number of job-related errors the employee has committed on t Job Satisfaction The level of job satisfaction by the employee (very satisfied, fairly s No of Work Absences The number of days the employee has been absent from work in a g Vacation Hours The number of vacation hours accrued by the employee in a given y Work Experience The number of years the employee has been working in the compan Gender The gender of the employee (male or female). Marital Status The marital status of the employee (single, married, divorce, widow Education Level The highest level of education attained by the employee (pre-high s Job Status The current employment status of the employee (part-time or full-t Motivation Factors The highest factor that motivates an employee to work harder (vaca The following is a raw data obtai Only the responses of the first 12 employees are sho Refer to individual questio Work Department Frequency of Overtime Weekly Income

Job Satisfaction Least Likely 5 Very Satisfied 5 245.45 17 Most Likely 14 Fairly Satisfied 6 200.30 18 Fairly Likely 20 Not Satisfied 2 204.75 13 Not At All 25 Very Satisfied 0 160.50 13 Least Likely 20 Not Satisfied 6 204.00 13 Least Likely 30 Very Satisfied 0 220.10 16 Most Likely 26 Fairly Satisfied 0 110.00 11 Most Likely 20 Very Satisfied 8 122.45 13 Least Likely 39 Fairly Satisfied 10 65.00 2 Least Likely 8 Very Satisfied 7 220.15 16 Fairly Likely 15 Fairly Satisfied 4 200.00 14 Fairly Likely 20 Not Satisfied 10 85.50 13 er) administration, logistics) me, often) ars (most likely, fairly likely, least likely, not at all). the job. satisfied, not satisfied). given year. year. ny. w) school, high school, college/university and post-graduate) time) ation, health benefits, salary, promotion, flexible hours). ined from a survey of 60 employees of a particular company. own here to demonstrate the type of information collected from each employee. ons for the responses obtained from the 60 employees. Likely To Change Job No of Job Errors No of Work Absences Vacation Hours Work Experience

Gender Education Level Job Status Female Single Pre-High School Part-Time Salary Male Married High School Full-Time Vacation Female Married College/University Part-Time Work Hours Male Single Post Graduate Full-Time Promotion Male Married College/University Full-Time Vacation Female Married High School Part-Time Salary Female Married High School Part-Time Salary Male Widow High School Part-Time Salary Female Married Pre-High School Part-Time Salary Male Widow Pre-High School Full-Time Work Hours Female Divorce Pre-High School Full-Time Work Hours Male Married High School Full-Time Work Hours Marital Status Motivation Factors