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Descriptive Data Analysis
Descriptive data analysis (DDA) is conducted to determine what sort of distributions
processes produce. Statistics are computed and graphical displays are created to explore
the central tendency, spread, shape, outlier patterns, etc. This information is used to
help form theories of cause and effect that can then be examined more carefully with
SPC or designed experiments. The results are used to plan fact-based future process
improvement activities. DDA and EDA are often used together.
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Figure 22. Example of Combined DDA and EDA Analysis
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Portions of MINITAB Statistical Software input and output contained in this book are printed with
permission of Minitab Inc.
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