R for statistics
Material type: TextPublication details: Boca Raton CRC 2012Description: 306 pISBN: 9781439881453Subject(s): R (Computer program language) | Statistics--Data processing | Statistics--Computer programs | Mathematical statistics--Data processingDDC classification: 519.50285 Summary: Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples. Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R. Focusing on the R software, the first section covers: Basic elements of the R software and data processing Clear, concise visualization of results, using simple and complex graphs Programming basics: pre-defined and user-created functions The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including: Regression methods Analyses of variance and covariance Classification methods Exploratory multivariate analysis Clustering methods Hypothesis tests After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.Item type | Current library | Collection | Call number | Status | Date due | Barcode |
---|---|---|---|---|---|---|
BK | Kannur University Central Library Stack | Stack | 519.50285 RFO (Browse shelf (Opens below)) | Available | 58893 |
Although there are currently a wide variety of software packages suitable for the modern statistician, R has the triple advantage of being comprehensive, widespread, and free. Published in 2008, the second edition of Statistiques avec R enjoyed great success as an R guidebook in the French-speaking world. Translated and updated, R for Statistics includes a number of expanded and additional worked examples.
Organized into two sections, the book focuses first on the R software, then on the implementation of traditional statistical methods with R.
Focusing on the R software, the first section covers:
Basic elements of the R software and data processing
Clear, concise visualization of results, using simple and complex graphs
Programming basics: pre-defined and user-created functions
The second section of the book presents R methods for a wide range of traditional statistical data processing techniques, including:
Regression methods
Analyses of variance and covariance
Classification methods
Exploratory multivariate analysis
Clustering methods
Hypothesis tests
After a short presentation of the method, the book explicitly details the R command lines and gives commented results. Accessible to novices and experts alike, R for Statistics is a clear and enjoyable resource for any scientist.
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