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Data Analysis Using SAS, by Chao-Ying Joanne Peng
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Data Analysis Using SAS offers a comprehensive core text focused on key concepts and techniques in quantitative data analysis using the most current SAS commands and programming language. The coverage of the text is more evenly balanced among statistical analysis, SAS programming, and data/file management than any available text on the market. It provides students with a hands-on, exercise-heavy method for learning basic to intermediate SAS commands while understanding how to apply statistics and reasoning to real-world problems.
Designed to be used in order of teaching preference by instructor, the book is comprised of two primary sections: the first half of the text instructs students in techniques for data and file managements such as concatenating and merging files, conditional or repetitive processing of variables, and observations. The second half of the text goes into great depth on the most common statistical techniques and concepts - descriptive statistics, correlation, analysis of variance, and regression - used to analyze data in the social, behavioral, and health sciences using SAS commands. A student study at www.sagepub.com/pengstudy comes replete with a multitude of computer programs, their output, specific details on how to check assumptions, as well as all data sets used in the book.
Data Analysis Using SAS is a complete resource for Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming courses across the social and behavioral sciences and health - especially those that carry a lab component.
- Sales Rank: #559362 in Books
- Brand: Brand: SAGE Publications, Inc
- Published on: 2008-08-28
- Original language: English
- Number of items: 1
- Dimensions: 9.90" h x 1.30" w x 6.80" l, 2.40 pounds
- Binding: Paperback
- 640 pages
- Used Book in Good Condition
Review
“Peng provides an excellent overview of data analysis using the powerful statistical software package SAS. This book is quite appropriate as a self-placed tutorial for researchers, as well as a textbook or supplemental workbook for data analysis courses such as statistics or research methods. Peng provides detailed coverage of SAS capabilities using step-by-step procedures and includes numerous comprehensive graphics and figures, as well as SAS printouts. Readers do not need a background in computer science or programming. Includes numerous examples in education, health sciences, and business.” (D. J. Gougeon 2009-03-02)
About the Author
C.Y. Joanne Peng (PhD, University of Wisconsin-Madison, Quantitative Methods with a minor in Statistics) is Professor of Educational Inquiry Methodology and Adjunct Professor of Statistics at Indiana University. Her research interests include logistic regression, missing data methods, and statistical computing using SAS, SPSS, BMDP, Minitab, CLUSTAN, Systat, and S+. She has published more than 50 refereed articles, book chapters, technical reports, and encyclopedia entries on applied statistics, psychometrics, and statistical computing. She is the author or co-author of two books on using SAS® for statistical analyses and received one BEST PAPER Award at a SAS® users annual conference. She has taught applied statistics and data analysis courses at major Research I universities for the past 20 years, including University of Wisconsin, University of Iowa, University of North Carolina, and Indiana University. She is a member of the American Statistical Association, American Educational Research Association, American Psychological Association, and the SAS Users Group International.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Great Introductory Reference
By C. Ferwerda
This book is a very well-written and well-organized introduction to SAS. Each chapter includes many examples, which are clearly explained. Rather than simply explaining how to write the code, the author guides the reader through interpreting the results. If you have no experience using SAS, this is a great resource, though more intermediate users may wish to look elsewhere for a more advanced book. For me, the most helpful chapter has been 'When Do You Stop Worrying and Start Loving Regression?', which guides you through writing the initial code (including variations for different types of models) as well as interpreting and testing the results. Highly recommended!
2 of 2 people found the following review helpful.
Exceptionally good
By I Teach Typing
I have been teaching SAS (and trying to find good SAS texts) for many years and I LOVE this book.
If you need to get one book on learning the SAS language get this. It covers everything from importing, to manipulating data (sorting and making new variables), and doing analysis with exceptionally easy to understand writing and very well annotated SAS code. The code, data sets and other materials are provided on the books website. So, you can easily follow along and produce output as you work your way through the book. The organization, index and table of contents are excellent.
The only down side to the book is that it was written with SAS 9.1.3 and the current release (9.2) adds a LOT of new tools for graphics. You can make up the difference with Statistical Graphics in SAS: An Introduction to the Graph Template Language and the Statistical Graphics Procedures or by digging in the most modern SAS support website.
While the lack of coverage of the new graphics procedures is an important drawback, there is no other book which covers the SAS programming language this well.
2 of 2 people found the following review helpful.
least helpful sas book I own
By apfphd
I bought this book when I was just beginning to learn SAS and I found it to be useless. I attempted to use it numerous times only to find what I needed didn't exist in text (I'm a social science researcher who often uses multivariate and univariate statistics) although occasionally the method was referenced in the text it did not give examples or clear explanations of how to write the code in SAS.
Save your money and don't buy this worthless book.
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