1. Exploratory Data Analysis 1.1. EDA Introduction 1.1.3. How Does Exploratory Data Analysis differ from Summary Analysis?
Summary	A summary analysis is simply a numeric reduction of a historic data set. It is quite passive. It's focus is in the past--historic data reduction. Quite commonly, its purpose is to simply arrive at a few key statistics (for example, mean and standard deviation) which may then either replace the data set on archives or carry the summary statistic along in a summary table. Summary statistics is simply passive recording and data reduction.
Exploratory	In contrast, EDA has as its broadest goal the desire to gain insight into the engineering/scientific process behind the data. Whereas summary statistics is passive and historic, EDA is active and futuristic. In an attempt to "understand" the process and improve it in the future, EDA uses the data as a "window" to peer into the heart of the process that generated the data. There is an archival role in the research and manufacturing world for summary statistics, but there is an enormously larger role for the EDA approach.