In statistics, Exploratory Data Analysis is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. 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. 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. 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.
There are a number of tools that are useful for EDA, but EDA is characterized more by the attitude taken than by particular techniques. Typical graphical techniques used in EDA are:
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