Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design; perform intermediate statistics, including multivariate statistics; interpret output; and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data; how to determine whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic analysis; how to compute and interpret post-hoc power; and an overview of basic statistics for those who need a review. Unique chapters on multilevel linear modeling; multivariate analysis of variance (MANOVA); assessing reliability of data; multiple imputation; mediation, moderation, and canonical correlation; and factor analysis are provided. SPSS syntax with output is included for those who prefer this format.
The new edition features:
• IBM SPSS version 22; although the book can be used with most older and newer versions
• New discusiion of intraclass correlations (Ch. 3)
• Expanded discussion of effect sizes that includes confidence intervals of effect sizes (ch.5)
• New information on part and partial correlations and how they are interpreted and a new discussion on backward elimination, another useful multiple regression method (Ch. 6)
• New chapter on how to use a variable as a mediator or a moderator (ch. 7)
• Revised chapter on multilevel and hierarchical linear modeling (ch. 12)
• A new chapter (ch. 13) on multiple imputation that demonstrates how to deal with missing data
• Updated web resources for instructors including PowerPoint slides and answers to interpretation questions and extra problems and for students, data sets, chapter outlines, and study guides.
IBM SPSS for Intermediate Statistics, Fifth Edition provides helpful teaching tools:
• all of the key SPSS windows needed to perform the analyses
• outputs with call-out boxes to highlight key points
• interpretation sections and questions to help students better understand and interpret the output
• extra problems with realistic data sets for practice using intermediate statistics
• Appendices on how to get started with SPSS, write research questions, and basic statistics.
An ideal supplement for courses in either intermediate/advanced statistics or research methods taught in departments of psychology, education, and other social, behavioral, and health sciences. This book is also appreciated by researchers in these areas looking for a handy reference for SPSS
"This text can be summed up in one exceedingly important word … practicality. Amidst a world of statistical complexity, the authors practically weave the use of SPSS, key considerations, interpretation, and writing up findings into one applied, very useful basket." – Robin K. Henson, University of North Texas, USA
"An excellent book that details the application of statistical procedures from exploratory data analysis and univariate techniques through to multivariate methods and multilevel modeling, this is an indispensable supplement to any advanced statistics or methods course."- Daniel J. Denis, University of Montana, USA
"This book is essential for students and researchers all over the world because it helps users learn about complex statistics and how to compute them. It is easy to understand even for non-native English speakers." - Krisztian Jozsa, University of Szeged, Hungary, EU
"I’ve been using this text to teach intermediate-level quantitative statistics to undergraduate psychology students for several years. I appreciate the thorough coverage of the SPSS output and the guidance that the authors provide with respect to the interpretation of that output." – Catherine I. Phillips, University of Calgary, Canada
1. Introduction 2. Data Coding and Exploratory Analysis (EDA) 3. Imputation of Missing Data 4. Several Measures of Reliability 5. Exploratory Factor Analysis and Principal Components Analysis 6. Selecting and Interpreting Inferential Statistics 7. Multiple Regression 8. Mediation, Moderation, and Canonical Correlation 9. Logistic Regression and Discriminant Analysis 10. Factorial ANOVA and ANCOVA 11. Repeated-Measures and Mixed ANOVAs 12. Multivariate Analysis of Variance (MANOVA) 13. Multilevel Linear Modeling/Hierarchical Linear Modeling Appendix A. Getting Started With SPSS and Other Useful Procedures D. Quick, M. Myers Appendix B. Review of Basic Statistics J.M. Cumming, A. Weinberg Appendix C. Answers to Odd Interpretation Questions