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Software for Data Analysis: Programming with R
Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in the face of the data flood that often faces statisticians. It is important to recognize the appropriate design, and to understand how to effectively implement it, being aware tha...
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Lenguaje: | eng |
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Springer
2008
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Acceso en línea: | https://dx.doi.org/10.1007/978-0-387-75936-4 http://cds.cern.ch/record/1315257 |
_version_ | 1780921337998475264 |
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author | Chambers, John |
author_facet | Chambers, John |
author_sort | Chambers, John |
collection | CERN |
description | Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in the face of the data flood that often faces statisticians. It is important to recognize the appropriate design, and to understand how to effectively implement it, being aware that the default settings from a computer package can easily provide an incorrect analysis. The goal of this book is to describe the principles that drive good design, paying attention to both the theoretical background and the problems arising from real experimental situations. Designs are motivated t |
id | cern-1315257 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2008 |
publisher | Springer |
record_format | invenio |
spelling | cern-13152572021-04-22T01:14:03Zdoi:10.1007/978-0-387-75936-4http://cds.cern.ch/record/1315257engChambers, JohnSoftware for Data Analysis: Programming with RMathematical Physics and MathematicsAlthough statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in the face of the data flood that often faces statisticians. It is important to recognize the appropriate design, and to understand how to effectively implement it, being aware that the default settings from a computer package can easily provide an incorrect analysis. The goal of this book is to describe the principles that drive good design, paying attention to both the theoretical background and the problems arising from real experimental situations. Designs are motivated tSpringeroai:cds.cern.ch:13152572008 |
spellingShingle | Mathematical Physics and Mathematics Chambers, John Software for Data Analysis: Programming with R |
title | Software for Data Analysis: Programming with R |
title_full | Software for Data Analysis: Programming with R |
title_fullStr | Software for Data Analysis: Programming with R |
title_full_unstemmed | Software for Data Analysis: Programming with R |
title_short | Software for Data Analysis: Programming with R |
title_sort | software for data analysis: programming with r |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-0-387-75936-4 http://cds.cern.ch/record/1315257 |
work_keys_str_mv | AT chambersjohn softwarefordataanalysisprogrammingwithr |