spreadsheet modeling and analysis

Project Description:

in the wake of the enron scandal in 2002, two public accounting firms, oscar anderson (oa) and trice-milkhouse-loopers (tml) merged (forming oatml) and are reviewing their methods for detecting management fraud during audits. the two firms had each developed their own set o questions that auditors could use in assessing management fraud.
to avoid a repeat of the problems faced by enron’s auditors, oatml wants to develop an automated decision tool to assist auditors in predicting whether or not their clients are engaged in fraudulent management practices. this tool would basically ask an auditor all the oa or tml fraud detection questions and then automatically render a decision about whether or not the client company is engaging in fraudulent activities. the decision problem oatml faces is really two-fold: 1) which of the two sets of fraud detection questions are best at detecting fraud? and, 2) what’s the best way to translate the answers to these questions into a prediction or classification about management fraud?
to assist in answering these questions, the company has compiled an excel spreadsheet that contains both the oa and tml fraud detection questions and answers to both sets of questions based on 382 audits previously conducted the two companies (see sheets oa and tml, respectively). (note: for all data 1 = yes, 0 = no). for each audit, the last variable in the spreadsheet indicates whether or not the respective companies were engaged in fraudulent activities (i.e., 77 audits uncovered fraudulent activities, 305 did not). you have been asked to perform the following analysis and provide a recommendation as to what combination of fraud questions oatml should adopt.
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Project Stats:

Price Type: Fixed

Project Budget: $50 to $100
Refunded
Total Proposals: 3
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