1.
Exploratory Data Analysis
1.2. EDA Assumptions
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Testing Underlying Assumptions Helps Assure the Validity of Scientific and Engineering Conclusions | Because the validity of the final scientific/engineering conclusions is inextricably linked to the validity of the underlying univariate assumptions, it naturally follows that there is a real necessity that each and every one of the above four assumptions be routinely tested. | ||
Four Techniques to Test Underlying Assumptions |
The following EDA techniques are simple, efficient, and powerful
for the routine testing of underlying assumptions:
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Plot on a Single Page for a Quick Characterization of the Data |
The four EDA plots can be juxtaposed for a quick look at the
characteristics of the data. The plots below are ordered
as follows:
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Sample Plot: Assumptions Hold |
This 4-plot of 500 normal random numbers reveals a process that has fixed location, fixed variation, is random, apparently has a fixed approximately normal distribution, and has no outliers. |
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Sample Plot: Assumptions Do Not Hold |
If one or more of the four underlying assumptions do not hold,
then it will show up in the various plots as demonstrated in the
following example.
This 4-plot reveals a process that has fixed location, fixed variation, is non-random (oscillatory), has a non-normal, U-shaped distribution, and has several outliers. |