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10-SEPTEMBER-2008 16:47:15 - Exploratory data analysis Redirected from Exploratory analysis Exploratory data analysis EDA is an approach to analyzing data for the purpose of formulating hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses1. It was so named by John Tukey. Contents 1 EDA development 2 Techniques 3 History 4 Software 5 See also 6 Bibliography 7 Notes 8 References 9 External links 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 confusing the two types of analysis and employing them on the same set of data can lead to systematic bias owing to the issues inherent in testing hypotheses suggested by the data. The objectives of EDA are to: Suggest hypotheses about the causes 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.2 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.3 The principal graphical techniques used in EDA are: Box plot Histogram MultiVari chart Run chart Pareto chart Scatter plot Stem-and-leaf plot The principal quantitative techniques are: Median polish the Trimean Letter values Resistant line Resistant smooth Rootogram Graphical and quantitative techniques are: Multidimensional scaling Ordination History Many EDA ideas can be traced back to earlier authors, for example: Francis Galton emphasized order statistics and quantiles. Arthur Bowley used precursors of the stemplot and five-number summary Bowley actually used a seven-figure summary, including the extremes, deciles and quartiles, along with the median - see his Elementary Manual of Statistics 3rd edn., 1920, p.62 - he defines the maximum and minimum, median, quartiles and two deciles as the seven positions. Andrew Ehrenberg articulated a philosophy of data reduction see his book of the same name. 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. Data Desk, an EDA package from Data Description of Ithaca, New York. Fathom for high-school and intro college courses. JMP, an EDA package from SAS Institute. LiveGraph free real-time data series plotter. TinkerPlots for upper elementary and middle school students. SOCR provides a large number of free Internet-accessible tools for EDA. See also Anscombe's quartet, on importance of exploration Predictive analytics Structured data analysis statistics Bibliography Hoaglin, D C; Mosteller, F Tukey, John Wilder Eds 1985. Exploring Data Tables, Trends and Shapes. ISBN 0-471-09776-4. Hoaglin, D C; Mosteller, F Tukey, John Wilder Eds 1983. Understanding Robust and Exploratory Data Analysis. ISBN 0-471-09777-2. Tukey, John Wilder 1977. Exploratory Data Analysis. Addison-Wesley. ISBN 0-201-07616-0. Velleman, P F Hoaglin, D C 1981 Applications, Basics and Computing of Exploratory Data Analysis ISBN 0-87150-409-X Notes ^ And roughly the only mechanism for suggesting questions is exploratory. And once they're suggested, the only appropriate question would be how strongly supported are they and particularly how strongly supported are they by new data. And that's confirmatory., A conversation with John W. Tukey and Elizabeth Tukey, Luisa T. Fernholz and Stephan Morgenthaler, Statistical Science Volume 15, Number 1 2000, 79-94. ^ Konold, C. 1999. Statistics goes to school. Contemporary Psychology, 441, 81-82. ^ 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, 341, Feb., 1980, pp. 23-25. 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 Miner3D EDA and visualization 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 EDA software for high dimensional non-linear data Visulab free interactive software for high dimensional non-spatial / non-temporal data with interactive EDA and visualization XLisp-Stat free software and Lisp based EDA development framework for Mac, PC and X Window Experimental Data Analyst Mathematica application package for EDA FactoMineR free exploratory multivariate data analysis software linked to R Retrieved from http://en..org/wiki/Exploratory_data_analysis Categories: Data analysis Views Article Discussion this page History Personal tools Log in / create account Navigation Main page Contents Featured content Current events Random article Search Go Search Interaction Community portal Recent changes Contact Donate to Help Toolbox What links here Related changes Upload file Special pages Printable version Permanent link Cite this page Languages Deutsch Español 한국어 Polski Português This page was last modified on 30 August 2008, at 03:27
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