Quick guide to IBM SPSS : statistical analysis with step-by-step examples
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Bibliographic Information
Quick guide to IBM SPSS : statistical analysis with step-by-step examples
SAGE, c2020
3rd ed
- : pbk
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Includes bibliographical references and index
Description and Table of Contents
Description
A perfect supplement for an introductory statics course.
Quick Guide to IBM (R) SPSS (R): 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 (R) SPSS (R) 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 x 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
by "Nielsen BookData"