SPSS: A User-Friendly Approach for Version 22

In this comprehensive introduction to SPSS, Jeffery Aspelmeier and Thomas Pierce explain the procedures and concepts of SPSS in a way that is easy to understand and vividly illustrated with cartoon-based scenarios. SPSS: A User-Friendly Approach goes beyond providing instructions on the mechanics of conducting data analysis and develops a student’s conceptual and applied understanding of quantitative techniques. Readers also learn how to complete a procedure and ensure that the results are statistically meaningful.

Jeffery Aspelmeier is currently a professor in the Department of Psychology at Radford University, where he has been teaching since 1999. He earned his B.S.Ed. in Secondary Education from Southwest Missouri State University, and his M.A. and Ph.D. in Social Psychology from Kent State University. His research interests focus on adult attachment and social cognition. When not writing statistics textbooks for fun, he likes to travel and ski with his wife Kim, canoe with his dog Cassidy, backpack on the Appalachian Trail with friends, and play banjo with anyone who will tolerate it (which typically does not include Kim or Cassidy).  Thomas Pierce is a professor in the Department of Psychology at Radford University. He has been teaching statistics and research methods since coming to Radford in 1992. He has a B.A. in Psychology from McGill University and a Ph.D. in Psychology from the University of Maine. He was also a postdoctoral fellow in the Center for the Study of Aging at Duke University Medical Center. His research interests are in the areas of aging and cognitive function, stress and human performance, and time series analysis of behavioral and physiological data.

1. Introduction to SPSS: A User-Friendly Approach
2. Basic Operations
3. Finding Sums
4. Frequency Distributions and Charts
5. Describing Distributions
6. Compute Statements: Reversing Scores, Combining Scores, and Creating z Scores
7. Comparing Means in SPSS (t Tests)
8. One-Way ANOVA: Means Comparison with Two or More Groups
9. Factorial ANOVA
10. Repeated-Measures Analysis of Variance
11. Regression and Correlation
12. Multiple Regression
13. Chi-Square
14. Reliability
15. Factor Analysis