The case study based on University Rating Systems and Carnegie Rating systems required to identify what types of organizations would be most likely to fraudulent report data. The data give a lot of information, but you should focus mostly on doctoral degrees achivement and how they might commit fraud.
1. Big Data and Fraud Project is the instruction for this case study
2. Combined_carn2 excel sheet gives a lot of data information, but you only need to focus at least 3 variables to doctral degree/ scholarship, falcuty, expenditure per falcuty. There might be more variables you want to use to analyze. However, if it doesn’t necessary, you can delete most of the column in the excel sheet. “ONLY choose related variables to analyze”
3. CCIHE2021-Research_Activity_Index: regarding “Scatter plot”sheet, you can choose any universities near the red line which shows those university just achieve R1 ranking. Thus, they might have more potential to commit fraud.
4. CCIHE2021-PublicData : This file explain all the abbriviate word from the “Combined_carn 2” excel sheet, so it easy for you to choose specific variables needed to analyze.
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