Marasinghe, M: SAS for Data Analysis
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Specificații
ISBN-13: 9781489987723
ISBN-10: 148998772X
Pagini: 572
Ilustrații: XII, 558 p. With 100 SAS Programs.
Dimensiuni: 155 x 235 x 31 mm
Greutate: 0.86 kg
Ediția:2008
Editura: Springer Verlag GmbH
Locul publicării:New York, NY, United States
ISBN-10: 148998772X
Pagini: 572
Ilustrații: XII, 558 p. With 100 SAS Programs.
Dimensiuni: 155 x 235 x 31 mm
Greutate: 0.86 kg
Ediția:2008
Editura: Springer Verlag GmbH
Locul publicării:New York, NY, United States
Public țintă
Professional/practitionerCuprins
Introduction 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.
Textul de pe ultima copertă
This 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 textssupplemented 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.
Many of the standard topics covered in statistical methods textssupplemented 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.
Caracteristici
Although there are several books on SAS, this book covers a wider array of topics and at a greater depth Includes supplementary material: sn.pub/extras
Notă biografică
Mervyn G. Marasinghe, PhD, is Associate Professor Emeritus of Statistics at Iowa State University, where he has taught courses in statistical methods and statistical computing. He has taught a data analysis course based on SAS for over 35 years and offered workshops and short-courses on various aspects of SAS including traditional SAS programming, SAS Enterprise Guide, SAS Enterprise Miner, and JMP for many years to both university audiences and non-academic participants. Kenneth J. Koehler, PhD, is University Professor of Statistics at Iowa State University, where he teaches courses in statistical methodology at both graduate and undergraduate levels and primarily uses SAS to supplement his teaching.