Discussion in 'General Anayltics' started by Nasif, Apr 21, 2012.
From single case studies to general rules, from big data to little exceptions
Two tendencies that I have encountered as people respond to data (in excess or in shortage) would be that of (1) ascribing rules to the exceptions (i.e., inferring general rules from single case studies), or (2) asserting exceptions to the rules (i.e., highlighting slim exceptions when presented with big data patterns).
I think of these tendencies as biases, because I believe they may represent some underlying processing errors our brains fall into when dealing with data, particularly given the context within which the analyses take place.
Ideally, we should be responding quite differently, and oppositely, than these two tendencies when analyzing data.
Case studies should engage our understanding of exceptions, or the exceptional aspects of a specific situation.
Big data should trigger our pursuit of general patterns, or the unexceptional things that a wide range of cases might have in common.
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