Data Analysis Using SAS Enterprise Guide
- 3h 41m
- A. J. Guarino, Glenn Gamst, Lawrence S. Meyers
- Cambridge University Press
- 2009
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.
About the Authors
Lawrence S. Meyers is Professor of Psychology at California State University, Sacramento. He teaches undergraduate and graduate courses in research design, data analysis, data interpretation, testing and measurement, and the history and systems of psychology. He was the coauthor of a textbook on research methods in the 1970s, has recently coauthored books on multivariate research design and analysis of variance, and has more than three dozen publications; some of his relatively recent work has been in areas such as measurement and testing and positive psychology. He received his doctorate from Adelphi University and worked on a National Science Foundation Postdoctoral Fellowship at the University of Texas, Austin and Purdue University.
Glenn Gamst is Professor and Chair of the Psychology Department at the University of La Verne, where he teaches the doctoral advanced statistics sequence. He received his doctorate from the University of Arkansas in experimental psychology. His research interests include the effects of multicultural variables, such as client–therapist ethnic match, client acculturation status and ethnic identity, and therapist cultural competence, on clinical outcomes. Additional research interests focus on conversation memory and discourse processing.
A. J. Guarino is on the faculty at Alabama State University, where he teaches graduate statistics courses in the Psychology Department. He received his bachelor’s degree from the University of California, Berkeley, and he earned a doctorate in statistics and research methodologies from the University of Southern California through the Department of Educational Psychology.
In this Book
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SAS Enterprise Guide Projects
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Placing Data into SAS Enterprise Guide Projects
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Performing Statistical Analyses in SAS Enterprise Guide
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Managing and Viewing Output
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Sorting Data and Selecting Cases
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Recoding Existing Variables
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Computing New Variables
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Descriptive Statistics
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Graphing Data
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Standardizing Variables Based on the Sample Data
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Standardizing Variables Based on Existing Norms
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Detecting Outliers
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Assessing Normality
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Nonlinearly Transforming Variables in Order to Meet Underlying Assumptions
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Bivariate Correlation—Pearson Product–Moment and Spearman Rho Correlations
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Simple Linear Regression
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Multiple Linear Regression
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Simple Logistic Regression
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Multiple Logistic Regression
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Independent-Groups t Test
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Correlated-Samples t Test
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Single-Sample t Test
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One-Way Between-Subjects ANOVA
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Two-Way Between-Subjects Design
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One-Way Within-Subjects ANOVA
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Two-Way Mixed ANOVA Design
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One-Way Chi-Square
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Two-Way Chi-Square
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Nonparametric Between-Subjects One-Way ANOVA
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One-Way Between-Subjects Analysis of Covariance
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One-Way Between-Subjects Multivariate Analysis of Variance
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Factor Analysis
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Canonical Correlation Analysis
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References
