# A Step-by-Step Approach to Using SAS for Univariate & Multivariate Statistics

SAS Institute, 2005 - Computers - 514 pages
Updated for SAS 9, A Step-by-Step Approach to Using SAS for Univariate and Multivariate Statistics, Second Edition, is an easy-to-understand introduction to SAS as well as to univariate and multivariate statistics. Clear explanations and simple language guide you through the research terminology, data input, data manipulation, and types of statistical analysis that are most commonly used in the social and behavioral sciences. Providing practice data inspired by actual studies, this book teaches you how to choose the right statistic, understand the assumptions underlying the procedure, prepare the SAS program for the analysis, interpret the output, and summarize the analysis and results according to the format prescribed in the Publication Manual of the American Psychological Association. Step by step, authors Norm O'Rourke, Larry Hatcher, and Edward Stepanski demonstrate how to perform the following types of analysis: simple descriptive statistics, measures of bivariate association, t tests for independent samples and paired samples, ANOVA and MANOVA, multiple regression, principal component analysis, and assessing scale reliability with coefficient alpha. This text is ideally suited to students who are beginning their study of data analysis, and to professors and researchers who want a handy reference on their bookshelf.

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### Contents

 Basic Concepts in Research and DATA Analysis 1 Introduction to SAS Programs SAS Logs and SAS Output 21 Data Input 29 Working with Variables and Observations in SAS Datasets 57 Exploring Data with PROC MEANS PROC FREQ PROC PRINT and PROC UNIVARIATE 89 Measures of Bivariate Association 119 Assessing Scale Reliability with Coefficient Alpha 155 Independent Samples and Paired Samples 167
 Multivariate Analysis of Variance MANOVA with One Between Subjects Factor 279 OneWay ANOVA with One Repeated Measures Factor 299 Factorial ANOVA with Repeated Measures Factors and Between Subjects Factors 325 Multiple Regression 367 Principal Component Analysis 429 Choosing the Correct Statistic 483 Datasets 491 Critical Values of the F Distribution 495

 OneWay ANOVA with One Between Subjects Factor 209 Factorial ANOVA with Two Between Subjects Factors 237