A Conceptual Guide to Statistics Using SPSS

Elliot T. Berkman is Assistant Professor of Psychology and director of the Social and Affective Neuroscience Laboratory at the University of Oregon. He has been teaching statistics to graduate students using SPSS for the past six years. In that time, he has been awarded the UCLA Distinguished Teaching Award and the Arthur J. Woodward Peer Mentoring Award. He has published numerous papers on the social psychological and neural processes involved in goal pursuit. His research on smoking cessation was recognized with the Joseph A. Gengerelli Distinguished Dissertation Award. He received his PhD in 2010 from the University of California, Los Angeles. Steve P. Reise is professor, chair of Quantitative Psychology, and co-director of the Advanced Quantitative Methods training program at University of California, Los Angeles. Dr. Reise is an internationally renowned teacher in quantitative methods; in particular, the application of item response theory models to personality, psychopathology, and patient reported outcomes. In recognition of his dedication to teaching, Dr. Reise was named "Professor of the Year" in 1995-96 by the graduate students in the psychology department at UC Riverside, and was awarded the 2008 Psychology Department Distinguished teaching award. Most recently, in recognition of his campus-wide and global contributions, Dr. Reise was awarded the University of California campus-wide distinguished teaching award. Dr. Reise has spent the majority of the last twenty years investigating the application of latent variable models in general and item response theory (IRT) models in particular to personality, psychopathology and health outcomes data. In 1998, Dr. Reise was recognized for his work and received the Raymond B. Cattell award for outstanding multivariate experimental psychologist. Along with Dr. Susan Embretson, Dr. Reise has the leading textbook on item response theory called "Item Response Theory for Psychologists" (2000 and forthcoming). He received his Ph.D. from the Department of Psychology at the University of Minnesota.

“The most impressive part of this text is its comprehensiveness. It covers all of the major statistical analyses anyone would need to know about. I found it difficult to read at times because I was not given the figures to see in order to understand better the text. Also headings were not distinct and/or missing which would have made it easier to read. There are not many texts like this available so it would allow instructors some flexibility in choosing a text appropriate for their needs. At this point it is too advanced for my students but I might buy a personal edition as a reference for myself.”

• 1. Introduction2. Descriptive Statistics3. Chi-Squared Test4. Linear Correlation5. One- and Two Sample T-Tests6. One-way ANOVA7. Two- and Higher-way ANOVA8. Within-subject ANOVA9. Mixed-model ANOVA10. MANOVA11. Regression12. ANCOVA13. Factor and Components Analysis14. Psychometrics15. Non-parametric Tests16. Matrix Algebra17. Appendix on the General Formulation of Custom Contrasts using Syntax