I think we practiced a question similar to this, and it was about analyzing transaction amounts. So, vendor invoice amounts seem like a likely candidate.
I'm going to go with vendor invoice amounts. That financial data is more likely to follow Benford's Law compared to things like phone numbers or employee IDs.
I'm a bit unsure about this one. I know Benford's Law is used to detect anomalies, but I'm not sure which of these data sets would be the most applicable.
Vendor invoice amounts seem like the most obvious choice here. That's the kind of financial data that Benford's Law is often used to analyze for potential fraud.
Hmm, this one seems tricky. I'll need to think carefully about the principles of Benford's Law and which types of data are most likely to follow that distribution.
Vendor invoices, hands down. It's like a treasure trove of potential fraud just waiting to be uncovered. Plus, I heard the fraud examiner gets a bonus for every dodgy invoice they find.
Bank account numbers? Nah, that's too obvious. Gotta go with employee IDs - you never know what kind of sneaky stuff people might be up to with their own data.
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