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Exploratory Data Analysis
1.1. EDA Introduction 1.1.2. How Does Exploratory Data Analysis differ from Classical Data Analysis?


Classical  The "good news" of the classical approach is that tests based on classical techniques are usually very sensitivethat is, if a true shift in location, say, has occurred, such tests frequently have the power to detect such a shift and to conclude that such a shift is "statistically significant". The "bad news" is that classical tests depend on underlying assumptions (e.g., normality), and hence the validity of the test conclusions becomes dependent on the validity of the underlying assumptions. Worse yet, the exact underlying assumptions may be unknown to the analyst, or if known, untested. Thus the validity of the scientific conclusions becomes intrinsically linked to the validity of the underlying assumptions. In practice, if such assumptions are unknown or untested, the validity of the scientific conclusions becomes suspect.  
Exploratory  Many EDA techniques make little or no assumptionsthey present and show the dataall of the dataas is, with fewer encumbering assumptions. 