The present book, Data Analysis Using SAS Enterprise Guide, provides readers with an overview of Enterprise Guide, the newest point-and-click interface from SAS. SAS Enterprise Guide is a graphical user (point-and-click) interface to the main SAS application, having relatively recently replaced the Analyst interface, which itself had replaced the original Assist interface. Enterprise Guide makes it easier than ever to access many SAS statistical analyses without learning to write the SAS code underlying its procedures.
We have written this book for readers who have little or no knowledge of SAS Enterprise Guide but who may wish to employ it for statistical analysis. Some of these readers will be students in an introductory statistics or data-analysis course; other readers will have taken an introductory statistics course and possibly a research methods course at some time in their past; and still other readers may have had several statistics and research design courses as a part of their background.We have therefore included in this book a relatively wide range of statistical procedures to meet the needs of various readers. There are chapters devoted to the more basic procedures such as descriptive statistics, correlation and simple linear regression, tests, and one-way chi-square analysis. In addition, we have also included statistical procedures at a somewhat higher level; these include data transformations and other types of computations, multiple linear regression, logistic regression, and some analysis of variance designs. Finally, we have incorporated topics that are more advanced for those readers who might have the need to use such techniques as analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis.
This book presents the basic procedures for utilizing SAS Enterprise Guide to analyze statistical data. SAS Enterprise Guide is a graphical user interface (point and click) to the main SAS application. Each chapter contains a brief conceptual overview and then guides the reader through concrete step-by-step examples to complete the analyses. The eleven sections of the book cover a wide range of statistical procedures including descriptive statistics, correlation and simple regression, t tests, one-way chi square, data transformations, multiple regression, analysis of variance, analysis of covariance, multivariate analysis of variance, factor analysis, and canonical correlation analysis. Designed to be used either as a stand-alone resource or as an accompaniment to a statistics course, the book offers a smooth path to statistical analysis with SAS Enterprise Guide for advanced undergraduate and beginning graduate students, as well as professionals in psychology, education, business, health, social work, sociology, and many other fields.