1.
Exploratory Data Analysis
1.3. EDA Techniques


Graphical and Quantitative Techniques 
This section describes many techniques that are commonly
used in exploratory and classical data analysis. This list is by
no means meant to be exhaustive. Additional techniques (both
graphical and quantitative) are discussed in the other chapters.
Specifically, the product comparisons
chapter has a much more detailed description of many classical
statistical techniques.
EDA emphasizes graphical techniques while classical techniques emphasize quantitative techniques. In practice, an analyst typically uses a mixture of graphical and quantitative techniques. In this section, we have divided the descriptions into graphical and quantitative techniques. This is for organizational clarity and is not meant to discourage the use of both graphical and quantitiative techniques when analyzing data. 

Use of Techniques Shown in Case Studies  This section emphasizes the techniques themselves; how the graph or test is defined, published references, and sample output. The use of the techniques to answer engineering questions is demonstrated in the case studies section. The case studies do not demonstrate all of the techniques.  
Availability in Software  The sample plots and output in this section were generated with the Dataplot software program. Other general purpose statistical data analysis programs can generate most of the plots, intervals, and tests discussed here, or macros can be written to acheive the same result. 