Statistical Software


Statistical Software pdf

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BMDP Statistical Software


BMDP Statistical Software

Author: Wilfrid Joseph Dixon

language: en

Publisher: Univ of California Press

Release Date: 1983-01-01


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The Future of Statistical Software


The Future of Statistical Software

Author: National Research Council

language: en

Publisher: National Academies Press

Release Date: 1991-02-01


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This book presents guidelines for the development and evaluation of statistical software designed to ensure minimum acceptable statistical functionality as well as ease of interpretation and use. It consists of the proceedings of a forum that focused on three qualities of statistical software: richnessâ€"the availability of layers of output sophistication, guidanceâ€"how the package helps a user do an analysis and do it well, and exactnessâ€"determining if the output is "correct" and when and how to warn of potential problems.

Software for Data Analysis


Software for Data Analysis

Author: John Chambers

language: en

Publisher: Springer Science & Business Media

Release Date: 2008-06-14


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John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award. He is author or coauthor of the landmark books on S. Now he turns to R, the enormously successful open-source system based on the S language. R's international support and the thousands of packages and other contributions have made it the standard for statistical computing in research and teaching. This book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated. The techniques covered include such modern programming enhancements as classes and methods, namespaces, and interfaces to spreadsheets or data bases, as well as computations for data visualization, numerical methods, and the use of text data.