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Exploratory data analysis

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Exploratory data analysis (EDA) is that part of statistical practice concerned with reviewing, communicating and using data where there is a low level of knowledge about its cause system. It was so named by John Tukey. Many EDA techniques have been adopted into data mining and are being taught to young students as a way to introduce them to statistical thinking.

Tukey held that too much emphasis in statistics was placed on evaluating and testing given hypotheses (confirmatory data analysis) and that the balance was in need of redressing in favour of using data to suggest hypotheses to test. In particular, confusion of the two types of analysis and employing them on the same set of data can lead to bias owing to the issues endemic in testing hypotheses suggested by the data.

The objectives of EDA are to:

The principal graphical tools used in EDA are:

The principal quantitative tools are:

Software

Bibliography

 


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