Exploratory data analysis In statistics, exploratory data
analysis (EDA) is an approach to analyzing data sets to
summarize their main characteristics, often with visual methods.
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. Tukey's championing of
EDA encouraged the development of statistical computing
packages, especially S at Bell Labs. The S programming language
inspired the systems 'S'-PLUS and R. This family of statistical-
computing environments featured vastly i