Here we look at some analysis on a Computer Technology Company (TechCom) employee and their experience, education and their annual salary. In addition, the company examines various departments and their relationship with the employee profiles. The data is based on the records from 2003 to 2010.

a) Shown below is the table illustrating the number of employees from two different departments: Production and Engineering (P&E) and Purchasing by gender and the educational attainment (in years). Use Exhibit 1 below to answer the following questions. Exhibit 1 Department Production and Engineering Department Purchasing Count of Employee Gender Count of Employee Gender Education Female Male Grand Total Education 0 2 4 6 8 Grand Total 43 35 78 Grand Total Using the two pivot tables in Exhibit 1, (i) Calculate the proportion of the female and the proportion of the male employees from the - P&E department. Show all workings to 4 decimal places. (ii) Similarly, calculate the proportion of the female and male employees from the Purchasing department. Show all workings to 4 decimal places. (iii) From part (i) and (ii), compare the percentage of the employees rm the two departments. 1)) Next, we want to examine the variable of employee's experience and the distribution of employees. Pivot tables (Exhibit 2) below show the employee experience from E and Purchasing departments. Exhibit 2 Department Production and Engineering Department Purchasing Count of Employee Gender Count of Employee Gender Prior Experience Female Male Grand Prior Experience Female Male Grand (years) Total (years) Total 0-4 21.79% 15.38% 3?.18% 0-4 25.3?% 17.91% 43.28% ..... 59 21-79% 769% 2949% 5_9_1493% 1045%253?% ...... 1 0-14 1 154% \"-95%..- 2949% 10-14 14-93% 1194%268?% 15-20 0.00% 3.85% 3.85% IIIIIIIIIII 15-20 4.48% 0.00% 4.48% Grand Total 55.13% 44.87% 100.00% IIIIIIIIIII Grand Total 59.70% 40.30% 100.00% Based on the above reported probabilities, discuss how the employees prior experience affects the distribution of the employees as their experience increases. Give examples. c) The pivot table below (Exhibit 3) gives the employee's prior experience by employees' gender for all company's departments. Exhibit 3: % of Grand Total Department (All) Count of Employee Gender Prior Experience (years) Female Male Grand Total 0-4 23.04% 15.69% 38.73% 5-9 18.14% 9.80% 27.94% 10-14 13.73% 14.22% 27.94% 15-20 3.43% 1.96% 5.39% Grand Total 58.33% 41.67% 100.00% (i) What does the value 5.39 present? From this Exhibit 3, answer the following questions. \fExhibit 4. Employees' salaries by prior experience 100% 80% 60% 40% Count (%) 20% 0% 5.9 10.14 15.20 Prior Experience (Years) l050 ISO-100 l100-150 l150-200 For the following questions, refer to above Exhibit 4. (i) Does the prior experience really matter in terms of employee's salary? Discuss giving the evidence in terms of values and the percentage estimates. (ii) Which range of years of experience has the highest percentage of group of annual salaries? State the salary group and the percentage as well. (iii) Which is the most salary group with the most years of experience? What percentage is that group? e) The pivot table below (Exhibit 5), examines the distribution of employees' salaries by their prior experience for all departments. Exhibit 5 Department All Count of Employee Annual Salary ($'000) Prior Experience (years) 0-50 50-100 100-150 150-200 Grand Total 0-4 45 32 2 79 5-9 5 47 4 l 5 7' 1 0- 14 36 2 1 5 7 15-20 3 7 l 1 1 Grand Total 50 118 34 2 204 Here we want to fmd out if the employees' prior years of experience is independent of their annual salaries. From Exhibit 5, write down a probability statement that would support that relationship If these two variables were independent