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Review
"a concise but simple manual for using SAS. It has put thousands of pages of SAS manuals in less than 400 pages of a paperbackdescribes the use of SAS Version 8.1 in the Microsoft Windows Environment. However, the programming part can be used in almost any environment The authors have again done an excellent job of explaining each statement as well as the resulting output In summary, the handbook introduces SAS programming through a number of datasets of varied complexity, makes the datasets suitable for analysis through programming statements, then uses SAS procedures for analysis. SAS procedures and the resulting outputs are properly explained, and suggestions for appropriate analyses are provided where necessary. Overall, I consider this an excellent handbook for a beginning SAS user. Statisticians and nonstatisticians can both benefit from this book." -The American Statistician, November 2002 "The aim of the book - to provide an easy to read reference for new users of SAS without having to resort to trawling through the manuals -- is well met. I feel that this would be a very good starting point for any student or researcher who wishes to learn the basics about the statistical techniques covered and how they can be programmed in SAS. The examples provided in the book cover a good range of data situations and analysis techniques." -M. K. Smith, Biometrics, June 2002
Product Description
Fully revised to reflect SAS Version 8.1, the second edition of this popular handbook gives concise, straightforward descriptions of how to conduct a range of statistical analyses. The authors have updated and expanded every chapter in this edition and incorporated a significant amount of new material. The book now contains more graphical material, more and better data sets within each chapter, more exercises, and more statistical background for each method. Additional topics include data description and simple inference for categorical variables, the general linear model, longitudinal data, and fitting mixture distributions by maximum likelihood.
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Customer Reviews
Most Helpful Customer Reviews
Format:Paperback
Really good handbook to keep at the side of your desk. However its not comprehensive, so some googling is still required.
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
9 reviews
40 of 42 people found the following review helpful
Good overview of implementations and methods
21 Oct 2002
Format:Paperback|Amazon Verified Purchase
This book is a good overview of how to implement in SAS some of the statistical methods you've probably already read about. I had done a lot of reading on factor analysis and clustering for my dissertation and needed a way to implement these methods in SAS. This book explains each method, then shows how to implement it using SAS. The data sets are from "The Handbook of Small Data Sets", which I got from my local university library. As I am a computer scientist and not a statistician, I found this book very helpful in putting together **the idea** of a particular statistical technique with the actual **implementation** of that technique. I have the first edition of this book also, and the second edition is much improved (especially the chapters on clustering and factor analysis).
28 of 28 people found the following review helpful
applications illustrated in SAS
24 Jan 2008
Format:Paperback
Brian Everitt is the author of several very well-written statistical texts. Among them he has written a number that show how to implement statistical analyses usimg statistical software packages. This second edition of "A Handbook of Statistical Analyses using SAS" he has coauthored with Geoff Der.
As a SAS user, I find this book very handy along with other similar texts that I have on the use of SAS. What is particularly good about this book is that it serves as a guide to the use of various SAS procedures and also as an illustration of appropriate statistical approaches to real applications using SAS.
It starts out with a nice introduction to the SAS prrogramming language and its syntax and progresses through simple descriptive statistics to categorical data analysis to regression and analysis of variance and then on to more advanced topics, including survival analysis, logistic regression, generalized linear models,longitudinal data analysis, principle components, factor analysis and cluster analysis. Appendices provide SAS MACROs and SAS solutions to exercises in the text.
What is particularly good about this book, that may set it apart from some of the others, is the expert statistical advice about the implementation and interpretation of results in SAS. They provide excellent scholarly references to the statistical literature to support their advice. As an example, I particularly liked their discussion of Type I and Type III sum of squares in the analysis of variance. They give a clear explanation of what each means and when they are equivalent and when they are different. In addition, they present their own view as to which is the appropriate one to use in given situations and support their view with quotes from other researchers. Opposing positions are also mentioned and referenced.
As a SAS user, I find this book very handy along with other similar texts that I have on the use of SAS. What is particularly good about this book is that it serves as a guide to the use of various SAS procedures and also as an illustration of appropriate statistical approaches to real applications using SAS.
It starts out with a nice introduction to the SAS prrogramming language and its syntax and progresses through simple descriptive statistics to categorical data analysis to regression and analysis of variance and then on to more advanced topics, including survival analysis, logistic regression, generalized linear models,longitudinal data analysis, principle components, factor analysis and cluster analysis. Appendices provide SAS MACROs and SAS solutions to exercises in the text.
What is particularly good about this book, that may set it apart from some of the others, is the expert statistical advice about the implementation and interpretation of results in SAS. They provide excellent scholarly references to the statistical literature to support their advice. As an example, I particularly liked their discussion of Type I and Type III sum of squares in the analysis of variance. They give a clear explanation of what each means and when they are equivalent and when they are different. In addition, they present their own view as to which is the appropriate one to use in given situations and support their view with quotes from other researchers. Opposing positions are also mentioned and referenced.
23 of 24 people found the following review helpful
Very readable and practical
2 Jan 2004
Format:Paperback
This book is very well written. Each topic is presented with an interesting example, including discussion. None of the topics are presented in great depth, so for example, this is not the book to use for learning factor analysis, or cluster analysis, etc. The real strength of the book is that it shows how to do the analysis using SAS in a clear and concise way. I would recommend this book highly for anyone who would like to get started using SAS.
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