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008			120329s2012 flua sb 001 0 eng d
020			_a9781439873663 (ebook : PDF)
040			_aBD-DhSAU _cBD-DhSAU
090			_aQA279 _b.H39 2012
092			_a519.502855133 _bH412
100	1		_aHay-Jahans, Christopher.
245	1	3	_aAn R companion to linear statistical models _h[electronic resource] / _cChristopher Hay-Jahans.
260			_aBoca Raton, Fla. : _bCRC Press, _cc2012.
300			_axvii, 354 p. : _bill.
504			_aIncludes bibliographical references and index.
505	0		_a1. Background -- 2. Linear regression models -- 3. Linear models with fixed-effects factors.
520			_a"Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cover methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. It also demonstrates applications of several pre-packaged functions for complex computational procedures"-- _cProvided by publisher.
520			_a"Preface This work (referred to as Companion from here on) targets two primary audiences: Those who are familiar with the theory and applications of linear statistical models and wish to learn how to use R or supplement their abilities with R through unfamiliar ideas that might appear in this Companion; and those who are enrolled in a course on linear statistical models for which R is the computational platform to be used. About the Content and Scope While applications of several pre-packaged functions for complex computational procedures are demonstrated in this Companion, the focus is on programming with applications to methods used for linear regression and designed experiments with up to two fixed-effects factors, including blocking variables and covariates. The intent in compiling this Companion has been to provide as comprehensive a coverage of these topics as possible, subject to the constraint on the Companion's length. The reader should be aware that much of the programming code presented in this Companion is at a fairly basic level and, hence, is not necessarily very elegant in style. The purpose for this is mainly pedagogical; to match instructions provided in the code as closely as possible to computational steps that might appear in a variety of texts on the subject. Discussion on statistical theory is limited to only that which is necessary for computations; common "rules of thumb" used in interpreting graphs and computational output are provided. An effort has been made to direct the reader to resources in the literature where the scope of the Companion is exceeded, where a theoretical refresher might be useful, or where a deeper discussion may be desired. The bibliography lists a reasonable starting point for further references at a variety of levels"-- _cProvided by publisher.
530			_aAlso available in print edition.
538			_aMode of access: World Wide Web.
650		0	_aLinear models (Statistics)
650		0	_aR (Computer program language)
655		7	_aElectronic books. _2lcsh
776	1		_z9781439873656 (hardback) _z1439873658 (hardback)
856	4	0	_uhttp://marc.crcnetbase.com/isbn/9781439873663 _qapplication/PDF
999			_c11855 _d11854