Statistical Data Analysis Using Your Personal Computer

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Overview

What should you see when you’re analyzing real data using one of the major statistical packages, such as SPSS, SAS or Microsoft Excel? This book will show you, and will walk you through the output from a variety of statistical outcomes, such as data reflecting a single common factor. Through the use of actual demonstrations, the authors supply readers with the computer programs necessary to simulate data sets with the statistical properties (usually multivariate) that are often assumed of real data. The reader is then shown how to analyze these data sets and how to interpret the results. The book begins with a general introduction to doing research and tips for using the three statistical packages. The authors next explore how to create data structures and perform univariate, bivariate, and multivariate simulations. They then show how to use the simulations to understand common statistical algorithms and their outputs when doing a basic correlation analysis, exploratory factor analysis, confirmatory factor analysis, multidimensional scaling, multiple regression, discriminate analysis, classification analysis and MANOVA. Throughout the book, the authors provide the reader with helpful guides, such as:
*Hint boxes to give readers tips for executing particular techniques using the statistical software packages.
*Steps that show each stage of a procedure, such as importing an Excel file into SAS.
*Problems end each chapter so the reader can practice the techniques described.
*Web Site with the SAS and SPSS programs and sample data.

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Editorial Reviews

Booknews
A textbook for a course teaching students of behavioral sciences how to analyze data using some of the software that has become available for personal computers. Bernstein and Rowe, presumably teachers somewhere, have revived demonstrations as an approach to teaching statistics. They assume students have at least some familiarity with the language and various topics taught in graduate statistics, multivariate analysis, and psychometric theory courses, but not to be experts in any of those fields. Annotation c. Book News, Inc., Portland, OR (booknews.com)
Joseph Roy Gillis
"A good resource for learning statistical concepts through using SPSS or SAS, and an excellent resource for an instructor teaching a statistical analysis course. The sequence of chapters builds logically from univariate to multivariate analysis. Each chapter provides a good explanation of the concepts to be illustrated. The book will be particularly useful for students and faculty in such programs as quantitative psychology, sociology, or public health."
Journal of Psychology in Africa

"In short, this book gives us an unparallel source of practical, tested and easy to use information and materials to help both instructors and students to use their fullest potential. "

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Product Details

  • ISBN-13: 9780761917816
  • Publisher: SAGE Publications
  • Publication date: 5/8/2001
  • Edition description: New Edition
  • Pages: 456
  • Product dimensions: 6.00 (w) x 8.90 (h) x 1.00 (d)

Meet the Author

Prof. Bernstein has a long background in both experimental psychology and the study of individual differences. Much of his work involves medical applications including opthalmology, pain management, and psychiatry. After spending many years at the University of Texas at Arlington, he joined the faculty at UT Southwestern because of his work on a collaborative project with Dr. A. John Rush, former associate chair of the Department of Clinical Sciences and professor of Psychiatry. He also holds an adjoint appointment in the School of Health Professions.

Nancy has been on the staff of the Office of Information Technology (OIT) since 1987 - ten of those years as the Manager of User Services. Her work has centered around applying the tools of mathematics, statistics, computers, and computer software to assist faculty, staff, and students in their research efforts. She now is Manager of Statistical Services.

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Table of Contents

Preface
1 Introduction 3
2 Hardware and Software Needs 15
3 Univariate Computer Simulations 57
4 Basic Correlational Simulations 95
5 Multivariate Correlational Simulations 137
6 Simulations With Categorical Data 185
7 Exploratory Factor Analysis 231
8 Confirmatory Factor Analysis and Related Procedures 269
9 Regression, Canonical Correlation, and Covariance Structure Analysis 295
10 Discriminant Analysis, Classification, and Multivariate Analysis of Variance 359
11 Analysis of Categorical Data 383
App Eigenanalysis of a Gramian Matrix 423
References 433
Author Index 437
Subject Index 441
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