Data Analysis Using SAS
- C.Y. Joanne Peng - Indiana University, USA
Designed to be used in order of teaching preference by instructor, the book is comprised of two 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 -áused to analyze data in the social, behavorial, and health sciences using SAS commands.
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.
“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.”
Shortcomings:
1) I am not quite pleased with the didactic presentation of the data analysis methods considered in book - one needs in any case some other statistical book to understand the methods.
2) I expected more from a book called "Data analysis...". You find there no more advanced data analysis methods than regression.
3) I was articularly looking for a statistical book with accompanied software SAS. This book is in fact about SAS language with some practical applications. Moreover, there is no connection to the SAS Enterprise Guide at all.
The strong point of the book I see in its detailed explanation of SAS language.
So, I would recommend this book for those who has already basic knowledge in statistical methods, for his analysis does not need any non-linear model and want to learn how to implement his model in SAS language.
But I found it not suitable to accompany any (basic or advanced) statistical course.
Despite offering several affordable packages, we were not allowed to require students to use SAS.
Excellent introduction to SAS and would be an excellent resource.
Sample Materials & Chapters
Chapter 1 - Why do you need to learn SAS for data analysis?
Chapter 13 - Analysis of variance