Exploratory Data Analysis
In Statistics, exploratory data analysis (EDA) is an approach to analysing data sets to summarize their main characteristics in easy-to-understand form, often with visual graphs, without using a statistical model or having formulated a hypothesis. Exploratory data analysis was promoted by John Tukey to encourage statisticians visually to examine their data sets, to formulate hypotheses that could be tested on new data-sets. Tukey's championing of EDA encouraged the development of statistical computing packages, especially S at BellLabs: The S programming language inspired the systems 'S'-PLUS and R. This family of statistical-computing environments featured vastly improved dynamic visualization capabilities, which allowed statisticians to identify outliers and patterns in data that merited further study. http://en.wikipedia.org/wiki/Exploratory_data_analysis
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