Editing Exploratory data analysis (section)

== Development ==
[[File:Data visualization process v1.png|right|350px|thumb|Data science process flowchart]]
[[John W. Tukey]] wrote the book ''Exploratory Data Analysis'' in 1977.<ref name="Tukey1977">{{cite book
| last = Tukey
| first = John W.
| year = 1977
| title = Exploratory Data Analysis | publisher = Pearson
| isbn = 978-0201076165| title-link = Exploratory Data Analysis
}}</ref> Tukey held that too much emphasis in statistics was placed on [[statistical hypothesis testing]] (confirmatory data analysis); more emphasis needed to be placed on using [[data]] to suggest hypotheses to test. In particular, he held that confusing the two types of analyses and employing them on the same set of data can lead to [[Systematic error|systematic bias]] owing to the issues inherent in [[testing hypotheses suggested by the data]].

The objectives of EDA are to:
*Enable unexpected discoveries in the data
*Suggest hypotheses about the [[causality|causes]] of observed [[phenomenon|phenomena]]
*Assess assumptions on which [[statistical inference]] will be based
*Support the selection of appropriate statistical tools and techniques
*Provide a basis for further data collection through [[survey sampling|surveys]] or [[design of experiments|experiments]]<ref>[https://web.archive.org/web/20170808064326/cll.stanford.edu/~willb/course/behrens97pm.pdf Behrens-Principles and Procedures of Exploratory Data Analysis-American Psychological Association-1997]</ref>

Many EDA techniques have been adopted into [[data mining]]. They are also being taught to young students as a way to introduce them to statistical thinking.<ref>{{cite journal |last=Konold |first=C. |year=1999 |title=Statistics goes to school |journal=Contemporary Psychology |volume=44 |issue=1 |pages=81–82 |doi= 10.1037/001949}}</ref>