What are you doing if you succumb to "overgeneralization" when analyzing data from metrics?

Question

Options

• AUsing data that is too broad to capture specific meanings.
• BPossessing too many types of data to perform a valid analysis.
• CUsing limited data in an attempt to support broad conclusions.
• DTrying to use several measurements to gauge one aspect of a program.

• A
  13% (8)
• B
  3% (2)
• C
  75% (46)
• D
  8% (5)

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