QBA.docx - LEBANESE AMERICAN UNIVERSITY ADNAN KASSAR SCHOOL...

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LEBANESE AMERICAN UNIVERSITY ADNAN KASSAR SCHOOL OF BUSINESS STUDIES Summer 2016 Case Study: Employee Data
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Executive Summary The Purpose of this project is to examine the existence of gender discrimination in the Lebanese Banking sector in terms salary and occupation. To do this, a sample of 120 employees from the Banking Sector in Lebanon is selected. Data collected include: Gender, Age, Education Level, Years of service, Occupation level and Salary. To address the problem of determining whether gender discrimination exists in the banking sector, several statistical methods and techniques were employed. First the data is coded and descriptive analysis is conducted. Next cross-tabulation was employed to assess the relationship between Gender and Education and between Gender and Occupation. Further descriptive analysis was used to compare salaries between male and female. Using these results several Hypothesis were suggested. Inferential Statistical methods were used to test these Hypotheses. The results indicate that in this sector of the economic, female are younger, more educated, paid less and less likely hold managerial positions.
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Introduction The banking sector in Lebanon is viewed as the most important sector of the economy; it has a major role in fueling the economic growth of Lebanon and ensuring the relative stability of the financial sector as a whole. It is believed that there is a wide range of gender discrimination in the Lebanese Banking Sector. To test evidence of gender discrimination, a sample of 120 employees. This report describes the employment status in this sector. By the end of 2008, the number of employees working in banks operating in Lebanon reached 18632. Out of this number, a sample of 120 employees is selected. The coded data used in this test include, as mentioned before, six variables concerning the status and positions of the employees. Using statistical techniques is essential to be able to analyze the collected data shown in Appendix. The statistical technique used is Megastat , which is a full-featured Excel add-in that performs statistical analysis with an Excel workbook. It performs basic functions, such as descriptive statistics , frequency distributions , and probability calculations as well as hypothesis testing , regression , and more. SPSS is another technique could be used to analyze the collected data. SPSS performs: Descriptive statistics : Cross tabulation , Frequencies , Descriptive Ratio Statistics Bivariate statistics: Means , Correlation Prediction for numerical outcomes: Linear regression
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Methodology The data collected will be analyzed using several statistical techniques using the statistical software packages Megastat and SPSS. The data contains six variables: The variables Age, Years of Service and Salary are numerical variables. The Gender, Education Level and Occupation Level are categorical, with Gender being nominal and the other two ordinals.
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