Exploratory data analysis

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Exploratory data analysis
Exploratory data analysis (EDA) is about looking at data to form hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses. It was so named by John Tukey.
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Exploratory Data Analysis
(EDA)
[J.W.Tukey, "Exploratory Data Analysis", 1977, Addisson Wesley].


(c) Copyright 1993 by Denis Howe

Electronic Statistics Textbook DictionaryDownload this dictionary
Exploratory Data Analysis (EDA)
As opposed to traditional hypothesis testing designed to verify a priori hypotheses about relations between variables (e.g., "There is a positive correlation between the AGE of a person and his/her RISK TAKING disposition"), exploratory data analysis (EDA) is used to identify systematic relations between variables when there are no (or not complete) a priori expectations as to the nature of those relations. In a typical exploratory data analysis process, many variables are taken into account and compared, using a variety of techniques in the search for systematic patterns.
For more information, see Exploratory Data Analysis (EDA) and Data Mining Techniques .

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