1.
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
as follows:


Sample Plot: Assumptions Hold 
This 4plot 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. 

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 4plot reveals a process that has fixed location, fixed variation, is nonrandom (oscillatory), has a nonnormal, Ushaped distribution, and has several outliers. 