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Quick Guide to IBM® SPSS®
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Quick Guide to IBM® SPSS®
Statistical Analysis With Step-by-Step Examples

Third Edition


August 2019 | 384 pages | SAGE Publications, Inc

A perfect supplement for an introductory statics course.

Quick Guide to IBM® SPSS®: Statistical Analysis With Step-by-Step Examples gives students the extra guidance with SPSS they need without taking up valuable in-class time. A practical, accessible guide for using software while doing data analysis in the social sciences, students can learn SPSS on their own, allowing instructors to focus on the concepts and calculations in their lectures, rather than SPSS tutorials. Designed to work across disciplines, the authors have provided a number of SPSS "step-by-step" examples in chapters showing the user how to plan a study, prepare data for analysis, perform the analysis and interpret the output from SPSS. 

The new Third Edition covers IBM® SPSS® version 25, includes a new section on Syntax, and all chapters have been updated to reflect current menu options along with many SPSS screenshots, making  the process much simpler for the user. In addition, helpful hints and insights are provided through the features "Tips and Caveats" and "Sidebars."

 

 
Preface & Acknowledgments
 
About the Authors
 
Chapter 1 • Introduction
Getting the Most Out of Quick Guide to IBM SPSS  
A Brief Overview of the Statistical Process  
Understanding Hypothesis Testing, Power, and Sample Size  
Understanding the p-Value  
Planning a Successful Analysis  
Guidelines for Creating Data Sets  
Preparing Excel Data for Import  
Guidelines for Reporting Results  
Downloading Sample SPSS Data Files  
Opening Data Files for Examples  
Summary  
References  
 
Chapter 2 • Describing and Examining Data
Example Data Files  
Describing Quantitative Data  
Describing Categorical Data  
Summary  
References  
 
Chapter 3 • Creating and Using Graphs
Introduction to SPSS Graphs  
Guidelines for Creating and Using Graphs  
Chart Builder  
Graphboard Template Chooser  
Legacy Plots  
Scatterplots  
Histograms  
Bar Charts  
Pie Charts  
Boxplots  
Summary  
References  
 
Chapter 4 • Comparing One or Two Means Using the t-Test
One-Sample t-Test  
Two-Sample t-Test  
Paired t-Test  
Summary  
References  
 
Chapter 5 • Correlation and Regression
Correlation Analysis  
Simple Linear Regression  
Multiple Linear Regression  
Summary  
References  
 
Chapter 6 • Analysis of Categorical Data
Contingency Table Analysis (r × c)  
Contingency Table Examples  
McNemar’s Test  
Mantel-Haenszel Meta-Analysis Comparison  
Tests of Interrater Reliability  
Goodness-of-Fit Test  
Other Measures of Association for Categorical Data  
Summary  
References  
 
Chapter 7 • Analysis of Variance and Covariance
One-Way ANOVA  
Two-Way Analysis of Variance  
Repeated-Measures Analysis of Variance  
Analysis of Covariance  
Summary  
References  
 
Chapter 8 • Nonparametric Analysis Procedures
Spearman’s Rho  
Mann-Whitney-Wilcoxon (Two Independent Groups Test)  
Kruskal-Wallis Test  
Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs  
Friedman’s Test  
Summary  
Reference  
 
Chapter 9 • Logistic Regression
Appropriate Applications for Logistic Regression  
Simple Logistic Regression  
Multiple Logistic Regression  
Summary  
References  
 
Appendix A: A Brief Tutorial for Using IBM SPSS for Windows
 
Appendix B: Choosing the Right Procedure to Use
 
Index

“Wonderful feedback from my graduate students using this textbook!”

Shlomo Sawilowsky
Wayne State University

“This book is an ideal resource and a guide for understanding basic concepts of statistics.” 

Vinayak Nahar
Lincoln Memorial University

“I really appreciate the detailed yet also practical approach. I also appreciate the comprehensive approach to the topics so that students are better grounded in how to think about their statistical analysis.”

Carrie Petrucci
Alliant International University

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Alan C. Elliott

Alan Elliott is the Director of the Statistical Consulting Center at Southern Methodist University within the Department of Statistical Science. Previously he served as a statistical consultant in the Department of Clinical Science at the University of Texas Southwestern Medical Center at Dallas for 30 years. Elliott holds master’s degrees in Business Administration (MBA) and Applied Statistics (MAS). He has authored or coauthored over 35 scientific articles and over a dozen books including the Directory of Microcomputer Statistical Software, Microcomputing with Applications, Using Norton Utilities, SAS Essentials, Applied Time Series... More About Author

Wayne A. Woodward

Wayne A. Woodward, Ph.D., is a Professor of Statistics and chair of the Department of Statistical Science at Southern Methodist University. He is a fellow of the American Statistical Association and was the 2004 recipient of the Don Owen award for excellence in research, statistical consulting, and service to the statistical community. In 2007 he received the Outstanding Presentation Award given by the Section on Physical and Engineering Sciences at the 2007 Joint Statistical Meetings in Salt Lake City, Utah. In 2003 he was named a Southern Methodist University Distinguished Teaching Professor by the university’s Center for Teaching... More About Author

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ISBN: 9781544360423
$30.00