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Mathematics - Probability Theory and Stochastic Processes | SAS for Data Analysis - Intermediate Statistical Methods (Reviews)

SAS for Data Analysis

Intermediate Statistical Methods

Marasinghe, Mervyn G., Kennedy, William J.

2008, XII, 558 p. With 100 SAS Programs.

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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 attaché 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)

 

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