View source for Exploratory data analysis

In [[statistics]], '''exploratory data analysis''' ('''EDA''') is an approach to analyzing data sets to summarize their main characteristics, often with [[Statistical graphics|visual methods]].

== Description ==

A statistical model can be used or not, but primarily EDA is for seeing what the [[data]] can tell us beyond the formal modeling or hypothesis testing task.

Exploratory data analysis was promoted by [[John Tukey]] to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments.

EDA is different from [[initial data analysis]] (IDA), which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed. EDA encompasses IDA.

== See also ==

* [[Anscombe's quartet, on importance of exploration]]
* [[Configural frequency analysis]]
* [[Data dredging]]
* [[Descriptive statistics]]
* [[Initial data analysis]]
* [[Predictive analytics]]
* [[Statistical graphics]]
* [[Structured data analysis (statistics)]]

== External links ==

* [https://en.wikipedia.org/wiki/Exploratory_data_analysis Exploratory data analysis] @ Wikipedia.org 

[[Category:Statistics]]