Data Analysis Using SAS Enterprise Guide

By: Lawrence S. Meyers, Glenn Gamst, A. J. Guarino

Paperback | 17 August 2009

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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.

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Introducing SAS Enterprise Guide
SAS Enterprise Guide projects
Placing data into SAS Enterprise Guide projects
Performing and Viewing Output
Performing statistical analyses in SAS Enterprise Guide
Managing and viewing output
Manipulating Data
Sorting data and selecting cases
Recoding existing variables
Computing new variables
Describing Data
Descriptive statistics
Graphing data
Standardizing variables based on the sample data
Standardizing variables based on existing norms
Score Distribution Issues
Detecting outliers
Assessing normality
Nonlinearly transforming variables in order to meet underlying assumptions
Correlation and Prediction
Bivariate correlation: Pearson product moment and Spearman rho correlations
Simple linear regression
Multiple linear regression
Simple logistic regression
Multiple logistic regression
Comparing Means t Tests
Independent groups t test
Correlated samples t test
Single sample t test
Comparing means ANOVA
One-way between subjects analysis of variance
Two-way between subjects design
One-way within subjects analysis of variance
Two-way mixed ANOVA design
Nonparametric Procedures
One-way chi square
Two-way chi square
Nonparametric between subjects one-way ANOVA
Advanced ANOVA Techniques
One-way between subjects analysis of covariance
One-way between subjects multivariate analysis of variance
Analysis of Structure
Factor analysis
Canonical correlation analysis
Table of Contents provided by Publisher. All Rights Reserved.

Data Analysis Using SAS Enterprise Guide

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