- This is a project to test the depth and breadth of your understanding on business analytics. The instructor wants to see if you are able to apply the concepts and tools taught in class to the real business situation. First, you want to think about the managerial situations that you want to work on. Formulate hypotheses that you think relevant and important. Then search for reliable data that you can work with. There are many reliable and available data on the internet. It is important to find a good dataset because it will increase the validity and significance of your analysis and managerial implications. The instructor strongly encourages students to try to match several datasets and clean them and then visualize/analyze the data. By merging several data together, you can practice the data cleaning skills and feel the procedures involved in business analytics.
- It is important that you provide accurate and insightful interpretations. Statistics, charts and other tools are of little use without good interpretations
- This is an individual test. Do not collaborate with other students. Violation of academic integrity will not be tolerated.
- Submit your data, analysis, interpretation and analysis in a Word file.
|Part 1||The reliability of the dataset and database source. Match your data with multiple datasets (at least two). The more matching, the better it is. Students shouldn’t use sports-related data unless approved. Do you best to use business related data. Otherwise, you will need to justify the use of other data from other fields.||25|
|Part 2||Identify your research questions. Students are encouraged to make the hypotheses managerial and business-related. The research questions should be intriguing, insightful, and informative. Explain why you chose the research topic and justify the significance of the research questions. Back them up by convincing logic, past studies, and experiences.||15|
|Part 3||Construct hypotheses that you attempt to explore through this exam. Literature and logical reasoning must back up hypotheses. Define the variables clearly. Operationalize the variables in alignment with the hypotheses. It is crucial to precisely define a variable.||10|
|Visualize the data using various tools such as frequency chart, pivot table, pivot charts, and other visualization figures introduced in class. Use various analysis methods to slice and dice the data. Provide insightful visualizations to summarize your arguments.||25|
|Part 5||Run at least two analysis listed here: Factor Analysis, Regression Analysis, and Cluster Analysis. Students are desired to run combinations of analysis. Report and interpret the results. Does the statistics make sense? If not, why? What insight do you gain from the analyses? State managerial implications. What are the limitations of your analyses?||25|
- Please refer to the lecture slides, exercises, and data reference for data sources and visualization tools.
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