R for SAS and SPSS Users [recurso electrónico] / by Robert A. Muenchen.

Por: Muenchen, Robert A [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries Statistics and ComputingEditor: New York, NY : Springer New York, 2011Descripción: XXVIII, 686 p. 118 illus., 32 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9781461406853Tema(s): Statistics | Computer science | Data mining | Computer graphics | Mathematical statistics | Social sciences -- Methodology | Psychological tests and testing | Statistics | Statistics and Computing/Statistics Programs | Probability and Statistics in Computer Science | Data Mining and Knowledge Discovery | Computer Graphics | Psychological Methods/Evaluation | Methodology of the Social SciencesFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 519.5 Clasificación LoC:QA276-280Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Installing and Updating R -- Running R -- Help and Documentation -- Programming Language Basics -- Data Acquisition -- Selecting Variables -- Selecting Observations -- Selecting Variables and Observations -- Data Management -- Enhancing Your Output -- Generating Data -- Managing Your Files and Workspace -- Graphics Overview -- Traditional Graphics- Graphics with ggplot2 -- Statistics -- Conclusion.
En: Springer eBooksResumen: R is a powerful and free software system for data analysis and graphics, with over 4,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 50 programs written in all three packages, comparing and contrasting the packages' differing approaches. The glossary defines R terms using SAS/SPSS terminology and again using R terminology. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. The second edition adds 216 pages of new topics.  "I found the book extremely helpful…The material is laid out in a way that makes it very accessible. Because of this I recommend this book to any R user regardless of his or her familiarity with SAS or SPSS...For new R users it will demystify many aspects, and for existing R users it will have many answers to those questions you have been too afraid to ask in public." --The American Statistician  "… an excellent introduction to R…the book meticulously covers data management, data structures, programming, graphics and basic statistical analysis in R. The prose is clear, the examples tied to their SPSS and SAS analogs. The handling of both traditional and newer “ggplot2” graphics is comprehensive: SPSS and SAS users will undoubtedly find lots to like. " --Information Management   "As a long time SAS user this book makes the task of transition to R much more palatable and appealing. It also greatly reduces the time to get up and running in R effectively." --Technometrics “It is great to see this book in a second edition. It serves nicely as an introduction to R, irrespective of whether they are familiar with SAS or SPSS. I have long been a fan of programming by example and the book is full of excellent ones.” --Graham Williams, Author, Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery
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Existencias
Tipo de ítem Biblioteca actual Colección Signatura Copia número Estado Fecha de vencimiento Código de barras
Libro Electrónico Biblioteca Electrónica
Colección de Libros Electrónicos QA276 -280 (Browse shelf(Abre debajo)) 1 No para préstamo 378785-2001

Introduction -- Installing and Updating R -- Running R -- Help and Documentation -- Programming Language Basics -- Data Acquisition -- Selecting Variables -- Selecting Observations -- Selecting Variables and Observations -- Data Management -- Enhancing Your Output -- Generating Data -- Managing Your Files and Workspace -- Graphics Overview -- Traditional Graphics- Graphics with ggplot2 -- Statistics -- Conclusion.

R is a powerful and free software system for data analysis and graphics, with over 4,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most like SAS and SPSS and compares them to R's built-in functions. It steps through over 50 programs written in all three packages, comparing and contrasting the packages' differing approaches. The glossary defines R terms using SAS/SPSS terminology and again using R terminology. The table of contents and the index allow you to find equivalent R functions by looking up both SAS statements and SPSS commands. The second edition adds 216 pages of new topics.  "I found the book extremely helpful…The material is laid out in a way that makes it very accessible. Because of this I recommend this book to any R user regardless of his or her familiarity with SAS or SPSS...For new R users it will demystify many aspects, and for existing R users it will have many answers to those questions you have been too afraid to ask in public." --The American Statistician  "… an excellent introduction to R…the book meticulously covers data management, data structures, programming, graphics and basic statistical analysis in R. The prose is clear, the examples tied to their SPSS and SAS analogs. The handling of both traditional and newer “ggplot2” graphics is comprehensive: SPSS and SAS users will undoubtedly find lots to like. " --Information Management   "As a long time SAS user this book makes the task of transition to R much more palatable and appealing. It also greatly reduces the time to get up and running in R effectively." --Technometrics “It is great to see this book in a second edition. It serves nicely as an introduction to R, irrespective of whether they are familiar with SAS or SPSS. I have long been a fan of programming by example and the book is full of excellent ones.” --Graham Williams, Author, Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery

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