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This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
- Sales Rank: #1668532 in Books
- Published on: 2008-08-12
- Original language: English
- Number of items: 1
- Dimensions: 9.40" h x 1.20" w x 7.00" l, 2.40 pounds
- Binding: Hardcover
- 558 pages
- ISBN13: 9780387773711
- Condition: Used - Very Good
- Notes: 100% Satisfaction Guarantee. Tracking provided on most orders. Buy with Confidence! Millions of books sold!
Review
From the reviews:
"The authors have presented an exceptionally detailed and complete guide to using SAS to read and process data, make tables and plots, and fit linear models with fixed, random, or mixtures of fixed and random components. All procedures are illustrated with numerous data examples, and both the SAS commands and the output are explained in meticulous detail. And as one would expect, all of the data and SAS code used in the book may be downloaded from a website. . . .�for a student who needs to learn the details of using SAS to process data and fit classical linear models, this book would make an excellent choice." (Dirk F Moore, Journal of Biopharmaceutical Statistics (JBS), Issue #5, 2009)
"The authors provide an easily readable introduction into the SAS language, some of its basic statistical methods, and many applications for statistical linear modeling. . . .Very helpful are the many exercises in each chapter which make this book valuable for teaching at universities and colleges. . . . As of today, almost all test examples and data sets are available from the Web page accompanying the book." (Wolfgang M. Hartman, Journal of Statistical Software, Vol. 28, October 2008)
"The authors have presented an exceptionally detailed and complete guide to using SAS to read and process data, make tables and plots, and fit linear models with fixed, random, or mixtures of fixed and random components. A ll procedures are illustrated with numerous data examples, and both the SAS commands and the output are explained in meticulous detail. And as one would expect, all of the data and SAS code used in the book may be downloaded from a website. … But for a student who needs to learn the details of using SAS to process data and fit classical linear models, this book would make an excellent choice. " (Dirk F. Moore, Journal of Biopharmaceutical Statistics, 2009, Issue 5)
“Many universities offer graduate courses in applied statistics where the emphasis is on regression and design of experiments. These courses typically attach� individuals from a wide array of disciplines with the purpose being to equip students with some of the essentials of data analysis. Typically students have been exposed to one or more point-and-click statistical software packages along the way in their statistical training but their exposure to programming-sophisticated packages such as R and SAS is at best, limited. The authors of this text clearly have a great deal of experience teaching these types of applied statistics courses as they have put together a fine text. …The text is carefully written and well organized. The introduction to the SAS language is one of the best that I am aware of. …Owners of this book will be happy to have it on their shelf.” (The American Statistician, May 2010, Vol. 64, No. 2)
“This book illustrates how to use the SAS system for data analysis. … The book can be used as a textbook in an applied statistics course that covers the topics in multiple regression and analysis of variance and requires the use of SAS for performing statistical analysis. It can also be used as a reference by researchers and data analysts in the academic setting or industry for conducting statistical analysis using SAS.” (Weiming Ke, Technometrics, Vol. 53 (1), February, 2011)
From the Back Cover
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.
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.
About the Author
William J. Kennedy is Avalon Foundation Professor in the Humanities in the Department of Comparative Literature at Cornell University. He is the author of several books, including The Site of Petrarchism: Early Modern National Sentiment in Italy, France, and England and Authorizing Petrarch.
Most helpful customer reviews
6 of 6 people found the following review helpful.
Good but dated already
By I Teach Typing
This book is designed to be a 2nd quarter graduate level statistics text for non-math majors. It features good writing, and well annotated code and output. Some sections have math up-to and including matrix algebra but strong math skills are not essential to use the book. The topics include:
Chapter 1: Introduction to SAS
Input and retain statements for loading and manipulating data
If you have the bad luck of getting data as a "complex" text file, where SAS can not automatically guess the format when you use the import procedure, this chapter alone makes the book worth the money. It is a GREAT discussion of reading complex text files.
Chapter 2: More on SAS Programing and Some Applications
Univariate statistics, proc plot, proc chart and proc tabulate for very early 1980s looking graphics
Chapter 3: Statistical Graphics Using SAS/Graph
Gplot and Gchart for qunatile, QQ plots, scatterplots, scatter matrices histograms for very early 1990s looking graphics
Chapter 4: Regression Models
Ordinary least squares regression and basic ANOVA (proc reg and proc anova), 4 types of sums of squares in SAS
Chapter 5: Analysis of Variance
Proc anova and glm for oneway anova, one way ancova and two way experiments
Chapter 6 Random and mixed effects modesls
Proc GLM and proc mixed for one and two way models
At the time of this review SAS 9.2 is out and it makes the graphics in this book (1/4 of the material) absolutely obsolete. If you are learning SAS with SAS 9.1.3 then this has very worthwhile coverage of the topics above. If you are using 9.2 you will want to sit down with the online documentation for the new graphics to look up the plots instead of using the code in the book. This would have been a 5 star book filling in topics not well covered in the SAS Press books if it was published 4 years ago. Sadly, it needs a 2nd edition already.
0 of 0 people found the following review helpful.
great book for learning SAS
By Y. Li
The book is in great condition.
This book is a great reference for SAS software which is a great tool of doing statistics analysis. The content is really useful and easy to follow
0 of 0 people found the following review helpful.
Good book
By siva kiran battepati
Very nice book for learners. Step by step instructions includes and examples are crystal clear too. Overall this is a good book for the price
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