Exploratory Data Analysis
1.2. EDA Assumptions
|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:|
|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
|Sample Plot: Assumptions Hold||
This 4-plot reveals a process that has fixed location, fixed variation, is random, apparently has a fixed approximately normal distribution, and has no outliers.
|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
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.