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3. 25 pts. a) What is meant by Large Data: b) give two examples including specifics of what the data is actually comprised of, and

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3. 25 pts. a) What is meant by Large Data": b) give two examples including specifics of what the "data" is actually comprised of, and c) describe how data analytics / mining / extraction software might be used to perform a forensic test over your two examples? 4. 10pts. In NO MORE THAN 20 words Describe how risk of incorrect acceptance AND risk of incorrect rejection is minimized

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