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EDA DEVELOPMENT

Tukey held that too much emphasis in Statistics was placed on Statistical Hypothesis Testing (confirmatory data analysis) more emphasis needed to be placed on using Data to suggest Hypotheses to test. In particular, he held that confusion of the two types of analysis and employing them on the same set of data can lead to Systematic Bias owing to the issues endemic in Testing Hypotheses Suggested By The Data .

The objectives of EDA are to:
  • Suggest hypotheses about the Cause s of observed Phenomena

  • Assess assumptions on which Statistical Inference will be based

  • Support the selection of appropriate statistical tools and techniques

  • Provide a basis for further data collection through Surveys or Experiments


Tukey's books were notoriously opaque, and so several attempts were made to popularise his EDA ideas. Prominent among these was the Statistics In Society (MDST242) course of The Open University .

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.


TECHNIQUES

There are a number of tools that are useful for EDA, but EDA is defined more by the attitude taken than the techniques used."Exploratory data analysis is an attitude, a flexibility, and a reliance on display, NOT a bundle of techniques, and should be so taught.", John W. Tukey, We Need Both Exploratory and Confirmatory, The American Statistician, Vol. 34, No. 1 (Feb., 1980), pp. 23-25.

The principal Graph ical techniques used in EDA are:


The principal Quantitative techniques are:


Graphical and quantitative techniques are:



HISTORY

Many EDA ideas can be traced back to earlier authors, for example:

The Open University course ''Statistics in Society'' (MDST 242), took the above ideas, and merged them with Gottfried Noether 's work, which introduced Statistical Inference via coin-tossing and the Median Test .

For details of the above, see John Bibby 's book ''HOTS: History of Teaching Statistics''.


SOFTWARE

  • CMU-DAP ( Carnegie-Mellon University Data Analysis Package, FORTRAN source for EDA tools with English-style command syntax, 1977)

  • Fathom (for high-school and intro college courses)

  • LiveGraph (free real-time data series plotter)

  • TinkerPlots (for upper elementary and middle school students)



SEE ALSO



BIBLIOGRAPHY

  • 1

  • 2

  • 3

  • Velleman, P F & Hoaglin, D C (1981) ''Applications, Basics and Computing of Exploratory Data Analysis'' ISBN 0-87150-409-X



REFERENCES


  • Leinhardt, G., Leinhardt, S., ''Exploratory Data Analysis: New Tools for the Analysis of Empirical Data'', Review of Research in Education, Vol. 8, 1980 (1980), pp. 85-157.



EXTERNAL LINKS

  • DataDesk (free-to-try commercial EDA software for Mac and PC)

  • GGobi (free interactive multivariate visualization software linked to R )

  • MANET (free Mac -only interactive EDA software)

  • Mondrian (free interactive software for EDA)

  • Orange (free component-based software for interactive EDA and machine learning)

  • ViSta (free interactive software based on Xlisp-Stat for EDA)

  • VisuMap (visualization software for high dimensional data)

  • XLisp-Stat (free software and Lisp based EDA development framework for Mac, PC and X Window)