Authors:
- Integrates SAS programming with complex data analysis applications
- Focuses on using SAS and statistical aspects of models and methods of analysis
- Introduction to SAS - beyond the basics and illustrated with numerous worked examples
- Advanced material suitable for a second course in applied statistics with every method explained using a SAS analysis to illustrate a real-world problem
- 15-20 problems in every chapter
- End of chapter exercises
- Solutions to exercises
- Downloadable SAS code and data sets
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
The book begins with an introduction beyond the basics of SAS, illustrated with non-trivial, real-world, worked examples. It proceeds to SAS programming and applications, SAS graphics, statistical analysis of regression models, analysis of variance models, analysis of variance with random and mixed effects models, and then takes the discussion beyond regression and analysis of variance to conclude.
Pedagogically, the authors introduce theory and methodological basis topic by topic, present a problem as an application, followed by a SAS analysis of the data provided and a discussion of results. The text focuses on applied statistical problems and methods. Key features include: end of chapter exercises, downloadable SAScode and data sets, and advanced material suitable for a second course in applied statistics with every method explained using SAS analysis to illustrate a real-world problem.
New to this edition:
•   Covers SAS v9.2 and incorporates new commands
•   Uses SAS ODS (output delivery system) for reproduction of tables and graphics output
•   Presents new commands needed to produce ODS output
•   All chapters rewritten for clarity
•   New and updated examples throughout
•   All SAS outputs are new and updated, including graphics
•   More exercises and problems
•   Completely new chapter on analysis of nonlinear and generalized linear models
•   Completely new appendix
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.
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.
Authors and Affiliations
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Department of Statistics, Iowa State University, Ames, USA
Mervyn G. Marasinghe, Kenneth J. Koehler
About the authors
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.
Bibliographic Information
Book Title: Statistical Data Analysis Using SAS
Book Subtitle: Intermediate Statistical Methods
Authors: Mervyn G. Marasinghe, Kenneth J. Koehler
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-3-319-69239-5
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer International Publishing AG, part of Springer Nature 2018
Softcover ISBN: 978-3-319-69238-8Published: 23 April 2018
eBook ISBN: 978-3-319-69239-5Published: 12 April 2018
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 2
Number of Pages: XIV, 679
Number of Illustrations: 19 b/w illustrations, 390 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Probability Theory and Stochastic Processes, Mathematical Software, Statistical Theory and Methods, Plant Sciences