Exploratory data analysis: Difference between revisions

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'''Exploratory [[data analysis]] (EDA)''' is that part of [[statistical practice]] concerned with reviewing, communicating and using [[data]] where there is a low level of knowledge about its [[cause system]]. It was so named by [[John Tukey]]. Many '''EDA''' techniques have been adopted into [[data mining]] and are being taught to young students as a way to introduce them to statistical thinking.

Tukey's books were notoriously opaque, and so several attempts were made to popularise his EDA ideas. Prominent among these was the [[Statistics in Society (MDST242)]] course of [[The Open University]].

Tukey held that too much emphasis in [[statistics]] was placed on evaluating and testing given [[hypothesis|hypotheses]] ([[confirmatory data analysis]]) and that the balance was in need of redressing in favour of using [[data]] to suggest [[hypothesis|hypotheses]] to test. In particular, confusion of the two types of analysis and employing them on the same set of data can lead to [[bias (statistics)|bias]] owing to the issues endemic in [[testing hypotheses suggested by the data]].