Exploratory Data Analysis (EDA): Difference between revisions

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Furthermore, EDA can be used to support the selection of appropriate statistical tools as well as to provide a basis for statistical inference and further data collection.  
Furthermore, EDA can be used to support the selection of appropriate statistical tools as well as to provide a basis for statistical inference and further data collection.  


Essential to EDA are graphical tools like ''box plots'', ''stem–and–leaf plots'' or ''scatter plots''.
Essential to EDA are graphical tools like ''box plots'', ''stem–and–leaf plots'', ''scatter plots'', or [[Timeline|timelines]].


== References ==
== References ==


[[Category: Glossary]]
[[Category: Glossary]]

Revision as of 06:52, 6 May 2005

Exploratory data analysis (EDA) was introduced by John Tukey as an approach to analyze data when there is only a low level of knowledge about its cause system as well as contextual information. EDA aims at letting the data itself influence the process of suggesting hypotheses instead of only using it to evaluate given (a priori) hypotheses.

Furthermore, EDA can be used to support the selection of appropriate statistical tools as well as to provide a basis for statistical inference and further data collection.

Essential to EDA are graphical tools like box plots, stem–and–leaf plots, scatter plots, or timelines.

References