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| Bill Luker Jr., PhD |
There is not much attention paid these days to data reliability and analytic validity (R&V) in quantitative thought and practice. Many data practitioners, especially those in Computer Science-IT Data Science (CS-IT Data Science), don’t get what the terms mean, especially for R&V work they might need to do routinely that is not done at all.
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