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

What are you doing if you succumb to "overgeneralization" when analyzing data from metrics?
A . Using data that is too broad to capture specific meanings.
B . Possessing too many types of data to perform a valid analysis.
C . Using limited data in an attempt to support broad conclusions.
D . Trying to use several measurements to gauge one aspect of a program.

View Answer

Answer: A

Explanation:

If you succumb to “overgeneralization” when analyzing data from metrics, you are using data that is too broad to capture specific meanings. For example, if you use a single metric such as “number of complaints” to measure customer satisfaction, you are ignoring other factors that may affect customer satisfaction such as quality of service, responsiveness, or loyalty. You are also assuming that all complaints are equally valid and important, which may not be the case. To avoid overgeneralization, you should use multiple metrics that are relevant, specific, and measurable for your objectives.

Reference: [IAPP CIPM Study Guide], page 59-60; [Avoiding Overgeneralization in Data Analysis]