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158 P r o c e s s C o n t r o l Q u a n t i f y i n g P r o c e s s Va r i a t i o n 159

Consideration Enumerative Study Analytic Study
Aim Parameter estimation Prediction
Focus Universe Process
Method of access Counts, statistics Models of the process
(e.g., flow charts, causes and
effects, mathematical models)
Major source of Sampling variation Extrapolation into the future
uncertainty
Uncertainty quantifiable? Yes No
Environment for the study Static Dynamic

Table 9.2 Important Aspects of Analytic Studies

In an analytic study the focus is on a process and how to improve it.
The focus is the future. Thus, unlike enumerative studies, which make
inferences about the universe actually studied, analytic studies are inter-
ested in a universe that has yet to be produced. Table 9.2 compares ana-
lytic studies with enumerative studies (Provost, 1988).
With regard to the analysis of processes, Deming (1986) comments:

Analysis of variance, t-tests, confidence intervals, and other statistical tech-
niques taught in the books, however interesting, are inappropriate because
they provide no basis for prediction and because they bury the information
contained in the order of production.
In organizations, processes are carried out as repeatable activities,
carried out time and time again. The element of time is lost in the enu-
merative tools of confidence intervals and hypothesis testing. While use-
ful for analyzing short-term data from a planned experiment, for example,
these enumerative tools pool the variation that occurs over time into a
single estimate of sample variation.
This is a persistent and unfortunate problem with the use of histo-
grams. Apparently, most practitioners learn that histograms are useful to
graphically show the shape of the data, which is fundamentally true.
Unfortunately, the shape of the data and the expected shape of the process
are completely different if the process is not stable. An example of this will
be shown shortly.

Acceptance Sampling
Acceptance sampling is a traditional quality control technique that is
applied to discrete lots or batches of a product. (A lot is a collection of
physical units; the term batch is usually applied to chemical materials).
The lot or batch is typically present ed to the inspection department by
either a supplier or a production depart ment. The inspection department

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