Data Analysis Using Sas Enterprise Guide

by Lawrence S. Meyers , Glenn Gamst , A. J. Guarino

• ISBN13: 9780521130073
• ISBN10: 0521130077
• Edition: 1st
• Format: Paperback
• Copyright: 2009-08-17
• Publisher: Cambridge University Press

Summary

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.

Table of Contents

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

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