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Attributes Data
Attribute
data is also known as "count" data. Typically, we will count the
number of times we observe some condition (usually something we don't like,
such as an error) in a given sample from the process. This is different
from measurement data in its resolution. Attribute data has less resolution,
since we only count if something occurs, rather than taking a measurement
to see how close we are to the condition. For example, Attributes data for
a health care process might include the number of patients with a fever,
whereas Variables data for the same process might be the measurement of
the patients' temperature.
Thus, Attributes data generally
provides us with less information than measurement (variables) data would
for the same process. Thus, for attributes data, we will generally not be
able to predict if the process is trending towards an undesirable state,
since it is already in this condition.
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