Any data measurements that are quantified
on an infinitely divisible numeric scale. Includes items like lengths,
diameters, temperatures, electrical measurements, or hours, (i.e. blue
print specifications, electrical specifications, etc.) that have
measurements like 2.34, 2.55, etc.
The opposite of Discrete
or Attribute data. These data types measure items like pass
or fail, leak or no leak, small, medium, or large, go or no go tests.
It may be easier and accurate
to use variable data in a six sigma
data types are required to use X-Bar and R-Bar
control charts. They usually have more
significance and thus research by Motorola would indicate that this data
type typically requires fewer samples than
discrete data types to have the same confidence level. Samples should be
taken using systematic sampling.