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001			5000088
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007			cr||||||||||||
008			110402s2008 xxu| s |||| 0|eng d
020			_a9780387773728
024	7		_a10.1007/978-0-387-77372-8 _2doi
035			_a978-0-387-77372-8
090			_amg
100	1		_aMarasinghe, Mervyn G _99224
245	1	0	_aSAS for Data Analysis _h[electronic resource]: _bIntermediate Statistical Methods/ _cby Mervyn G. Marasinghe, William J. Kennedy.
260			_aNew York: _bSpringer New York, _c2008.
300			_aXII, 554p. With 100 SAS Programs. _bdigital.
490	0		_aStatistics and Computing, _x1431-8784
505	0		_aIntroduction to SAS language -- More on SAS programming and some applications -- Statistical graphics using SAS/GRAPH -- Statistical analysis of regression models -- Analysis of variance models -- Analysis of variance: random mixed effects models -- Appendices -- References -- Index .
520			_aThis book is an integrated treatment of applied statistical methods, presented at an intermediate level, and the SAS programming language. It serves as an advanced introduction to SAS as well as how to use SAS for the analysis of data arising from many different experimental and observational studies. While there are many introductory texts on SAS programming, statistical methods texts that solely make use of SAS as the software of choice for the analysis of data are rare. While this is understandable from a marketability point of view, clearly such texts will serve the need of many thousands of students and professionals who desire to learn how to use SAS beyond the basic introduction they usually receive from taking an introductory statistics course. More recently, several authors in statistical methodology have begun to incorporate SAS in their texts but these books are limited to more specialized subjects. Many of the standard topics covered in statistical methods texts supplemented by advanced material more suited for a second course in applied statistics are included, so that specific aspects of SAS procedures can be illustrated. Brief but instructive reviews of the statistical methodologies used are provided, and then illustrated with analysis of data sets used in well-known statistical methods texts. Particular attention is devoted to discussions of models used in each analysis because the authors believe that it is important for users to have not only an understanding of how these models are represented in SAS but also because it helps in the interpretation of the SAS output produced. Mervyn G. Marasinghe is Associate Professor of Statistics at Iowa State University where he teaches several courses in statistics and statistical computing and a course in data analysis using SAS software. A former Associate Editor of the Journal Computational and Graphical Statistics, he has used SAS software for more than 30 years. William J. Kennedy is Professor Emeritus of Statistics at Iowa State University. A Fellow of the American Statistical Association and former Editor of The American Statistician and Journal of Computational and Graphical Statistics, he is coauthor of the book entitled Statistical Computing .
650		0	_aStatistics. _943790
650		0	_aMathematical statistics _943558
697			_aMatemáticas Gerais- _x(inclusive alguns textos elementares sobre assuntos específicos) _923752
700	0		_aKennedy, William J., _d1936- _922182
710	1		_aSpringerLink (Online service). _98857
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387773711
830		0	_aStatistics and computing _99225
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-77372-8
942			_2impa _cEBK
999			_aMARASINGHE, Mervyn G; KENNEDY, William J.,. <b> SAS for Data Analysis: </b> Intermediate Statistical Methods. New York: Springer New York, 2008. XII, 554p. With 100 SAS Prog (Statistics and Computing, 1431-8784). ISBN 9780387773728. Disponível em: <http://dx.doi.org/10.1007/978-0-387-77372-8 > _c38515 _d38515