Does there exist a link between gender and wage differential?
This assignment requires you to build and estimate a model using Microsoft Excel or specialist software to address a management problem. Please upload both your report and data analysis file on Moodle.
You are required to find a management decision problem in any company. Using Excel (or specialised software), conduct an analytics for the problem, and interpret the results. You are required to submit a technical report (1,500 words) that discusses the managerial problem, the results, their implications and makes recommendations for improvement.
Your report will be marked according to the following criteria: problem description; modelling and solution; discussion on the result; managerial recommendations.
The grade components will be approximately distributed as follows: Introduction (5%) Descriptive analysis (20%) Regression analytics (25%) Managerial interpretations and implications (40%) Conclusion (10%) Introduction In this section, you will identify your research question – based on the Excel Data you are assigned. It is important to give reasons for why you think it’s interesting to explore such question. Descriptive analysis: Import the raw data to the database, make sure it imported correctly, identify the main tables and relationships between, produce relevant visualizations. Regression analysis: Using appropriate regression models to address the managerial problem.
II. Steps to be taken
1. Please go to the module webpage in Unihub;
2. Go to the section named “ Individual Assignment”;
3. Upload the zip file to your laptop;
4. Open the file name “Assignment of Excel file” to individual student;
5. Identify the data file that is associated with your student ID.
6. Open the Excel file that you find in step 5. For example, if your student ID is associated with Data 2, then you will work on Data 2.
III. Description of the EXCEL data files:
The file P02_03.xlsx contains data from a survey of 399 people regarding an environmental policy.
Data 2: The file P02_07.xlsx includes data on 204 employees at the (fictional) company Beta Technologies.
Data 3: The data Lasagna Triers.xlsx is related to the buying behavior of customers. Data 4: Catalog Marketing.xlsx contains recent data on 1000 HyTex customers. Data 5: The file P03_63.xlsx contains financial data on 85 U.S. companies in the Computer and Electronic Product Manufacturing sector (NAICS code 334) with 2009 earnings before taxes of at least $10,000. Each of these companies listed R&D (research and development) expenses on its income statement. Data 6: The file P10_05.xlsx contains information about the human resources.
Data 7: This is data for Business Week’s top U.S. MBA programs in the MBA Data sheet of the file P11_14.xlsx. Data 8: The file P11_44.xlsx lists the test scores and performance ratings for a randomly selected group of employees. It also lists their seniority (months with the company) at the time of the performance rating.
IV. Some suggestions on how to proceed with the assignment The best way to think about this assignment is to consider it a simplified version of your master dissertation which you are going to do soon! As such, you can apply knowledge acquired from the Dissertation Module, and any other modules to work on the assignment. In what follows, I would like to provide you with some suggestions on how to explore the EXCEL data to write the report. Let’s assume you are given a data that have information about HR. In this data you have variables such as age, gender, work experience, education, salary, tenure and so on.
1. How to define a problem or research question? It is sufficient to define just one research question. In this example, you can propose a question such as “ Does there exist a link between gender and wage differential?”. In other words, you want to study whether female employees and male employees have the same salary level if they have the same level of education, work experience…. It is also important to elaborate on why you think this is an interesting and relevant question. To do so, it’s a good idea to incorporate some existing academic references that address the link between gender and salary.
2. How to do the data analysis
2.1. Descriptive analysis
You can report some measure of central tendency such as mean, median, standard deviation, frequency of the main variables in the Excel file;
2.2. Regression analysis In this example, salary would be the dependent variable. You then can run the regression using the techniques we talk in class.
3. Interpretation of the results
It’s important to provide some discussion on your findings. For example, if you find that the coefficient for men is positive i.e., men have higher salary than women. You can explain why this might be the case. Also, it’s good idea to make references to academic studies that may or may not support your results.
4. Recommendation What would be the managerial implications for your results? For example, if men have higher salary then women, what would you like to recommend either from the government’s policy perspective, and/or from the firm’s HR practices perspective.
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