000			01802nam a2200169 4500
020			_a9781439881453
082			_a519.50285 _bRFO
245			_aR for statistics
260			_aBoca Raton _bCRC _c2012
300			_a306 p.
520			_aAlthough 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.
650			_aR (Computer program language)
650			_aStatistics--Data processing
650			_aStatistics--Computer programs
650			_aMathematical statistics--Data processing
942			_cBK
999			_c66385 _d66385