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Take Web Data Analysis To The Next Level With PHP
By Paul Meagher - 2003-12-22 Page:  1 2 3 4 5 6 7 8 9 10 11 12 13


  • Download the source code used in this article.

  • Find future enhancements of this code at

  • Read "Simple linear regression with PHP: Part 1," by Paul Meagher. It offers examples of how to develop and apply a library of analytic models, focusing on a Simple Linear Regression algorithm package using PHP as the implementation language (developerWorks, March 2003).

  • Continue with "Simple linear regression with PHP: Part 2," as Paul Meagher shows how to add features to the package (from Part 1) to develop a useful data-analysis tool for small- to medium-sized datasets and includes more information about probability distribution functions (developerWorks, April 2003).

  • Take "Card sorting and cluster analysis" by Thomas Myer, an introductory-level tutorial designed to deliver card-sorting and cluster-analysis user-data-gathering statistical techniques to information architects and usability engineers (developerWorks, January 2001).

  • I would like to thank Dr. Tessema Astatkie for useful discussions on experimental methodology and Chi Square analysis; you'll find a cornucopia of articles on statistical analyses of data here.

  • Visit the R Project for Statistical Computing Web site for more on the open source statistics package R.

  • Explore the IBM Information Aggregation business pattern (or U2D pattern) for tools to capture, access, and manipulate data that is aggregated from multiple sources and tools to personalize data to suit user preferences, distill summary information from large volumes of data, use algorithms to identify trends hidden in data, and answer hypothetical "what-if" questions about potential business scenarios.

  • Review the TLTP/Steps Statistics Glossary 1.1 by Valerie Easton and John McCall. It offers a concise, interactive education in the definition of statistical terms in the following topic areas: presenting data; sampling; probability; confidence intervals; hypothesis testing; paired data, correlation, and regression; design of experiments; and more.

  • Find an introduction to the philosophy of experimentation and the part that statistics play in experimentation in the classic Statistics for Experimenters: An Introduction to Design, Data Analysis, and Model Building, by George Box, Stuart Hunter, and William G. Hunter (Wiley, 1978).

  • Read a classic work in the application of statistical procedures: Handbook of Parametric and Nonparametric Statistical Procedures, 3rd Ed., by David J. Sheskin (CRC Press, 2000).

  • Review the NIST/SEMATECH Engineering Statistics Internet Handbook, an invaluable reference to statistical analysis.

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First published by IBM developerWorks

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