IBM SPSS for Intermediate Statistics : Use and Interpretation, Fifth Edition

This book reviews how to choose the statistic based on the design, interpret output, and write about the results to help readers analyze data using SPSS 22. Readers learn to: assess data reliability; determine whether data meet the assumptions of statistical tests; and calculate and interpret effect sizes and power. Basic statistics is reviewed along with chapters on MLM, MANOVA, and factor analysis. The key SPSS windows needed to perform the analyses are provided along with annotated output, interpretation questions, and problems for review. Data sets, SPSS syntax, and instructors’ materials are on the web. This text is ideal for students and researchers in a variety of disciplines.

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.

• 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.

• 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