pg_0156
5.
Process Improvement
5.4.
Analysis of DOE data
5.4.2.
How to "look" at DOE data
The
importance
of looking at
the data with
a wide array
of plots or
visual
displays
cannot be
over-stressed
The right graphs, plots or visual displays of a dataset can uncover
anomalies or provide insights that go beyond what most quantitative
techniques are capable of discovering. Indeed, in many cases
quantitative techniques and models are tools used to confirm and extend
the conclusions an analyst has already formulated after carefully
"looking" at the data.
Most software packages have a selection of different kinds of plots for
displaying DOE data. Dataplot, in particular, has a wide range of
options for visualizing DOE (i.e., DEX) data. Some of these useful
ways of looking at data are mentioned below, with links to detailed
explanations in Chapter 1 (Exploratory Data Analysis or EDA) or to
other places where they are illustrated and explained. In addition,
examples and detailed explanations of visual (EDA) DOE techniques
can be found in section
5.5.9
.
Plots for
viewing the
response
data
First "Look" at the Data
Histogram of responses
q
Run-sequence plot (pay special attention to results at center
points)
q
Scatter plot (for pairs of response variables)
q
Lag plot
q
Normal probability plot
q
Autocorrelation plot
q
5.4.2. How to "look" at DOE data
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