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SAS for Data Analysis

Marasinghe, Mervyn G./Kennedy, William J.

ISBN 10: 0387773711 / ISBN 13: 9780387773711
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Titel: SAS for Data Analysis

Erscheinungsdatum: 2008

Einband: Soft cover

Zustand: New


Brand New, Unread Copy in Perfect Condition. A+ Customer Service! Summary: This book is an integrated treatment of applied statistical methods, presented at an intermediate level. It serves as an advanced introduction to the SAS programming language as well as demonstrating how to use SAS to analyse of a wide variety of data. Buchnummer des Verkäufers ABE_book_new_0387773711

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Inhaltsangabe: 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 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.

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