 | SAS for Data Analysis: Intermediate Statistical Methods (Statistics and Computing) |  |
| | Publisher: Springer | Publication: 2008, English | ISBN: 9780387773711 | Pages: 557 |
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 primarily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level statistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an understanding of basic concepts of statistical inference such as estimation and hypothesis testing.
Understandably, adequate time is not available in a first course in statistical 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 specifiers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
The basic theory of those statistical methods covered in the text is discussed briefly and then is extended beyond the elementary level. Particular attention has been given to topics that are usually not included in introductory courses. These include models involving random effects, covariance analysis, variable subset selection in regression methods, categorical data analysis, and graphical tools for residual diagnostics. However, a thorough knowledge of advanced theoretical material such as linear model theory will not be assumed or required to assimilate the material presented. | |
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