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

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


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About the Book

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."  

Table of Contents:
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

About the Author :
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 Analysis, and Statistical Analysis Quick reference Guidebook with SPSS Examples. Elliott has taught university-level courses in statistics, statistical consulting, and statistical computing for over twenty-five years.  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 Excellence, and he received the 2006-2007 Scholar/Teacher of the Year Award at SMU, an award given by the United Methodist Church. . Over the last 35 years he has served as statistical consultant to a wide variety of clients in the scientific community and has taught statistics courses ranging from introductory undergraduate statistics courses to graduate courses within the Ph.D. program in Statistics at Southern Methodist University. He has been funded on numerous research grants and contracts from government and industry to study such issues as global warming and nuclear monitoring.  He has authored or coauthored over 70 scientific papers and four books. 

Review :
"Wonderful feedback from my graduate students using this textbook!" "This book is an ideal resource and a guide for understanding basic concepts of statistics."  "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."


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Product Details
  • ISBN-13: 9781544360423
  • Publisher: SAGE Publications Inc
  • Publisher Imprint: SAGE Publications Inc
  • Edition: Revised edition
  • Language: English
  • Returnable: Y
  • Weight: 480 gr
  • ISBN-10: 1544360428
  • Publisher Date: 15 Oct 2019
  • Binding: Paperback
  • Height: 228 mm
  • No of Pages: 392
  • Sub Title: Statistical Analysis With Step-by-Step Examples
  • Width: 152 mm


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