Applied Statistics: From Bivariate Through Multivariate Techniques, Second Edition, provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. Author Rebecca M. Warner uses an applied approach that does not require formal mathematics; equations are accompanied by verbal explanations, and students are asked to think about the meaning of the equations. Each chapter presents a complete empirical research example to illustrate the application of a specific method, along with a glossary and comprehension questions to help students master each concept. SPSS examples are used throughout the book; however, the conceptual material will be helpful for users of different programs.
A companion site at www.sagepub.com/warner2e includes data sets for the student and a test bank and PowerPoint slides for the instructor.
Changes in the Second Edition
· All SPSS screen shots and output have been updated to IBM SPSS version 19.
· Chapter 4 (data screening) has brief new sections about examination of pattern in missing data, imputation of missing values, and problems with dichotomizing scores on quantitative variables.
· Chapter 9 (bivariate regression) now includes references to discussion of problems with comparison of standardized regression coefficients across groups.
· Chapter 10 includes a new section on inconsistent mediation as one type of suppression.
· Chapter 13 has new examples using bar graphs with error bars to report means in factorial ANOVA.
In the first edition, mediation was discussed briefly in chapters 10 and 11, and moderation / analysis of interaction in regression was introduced in chapter 12. In the second edition, this material has been moved into separate new chapters and substantially expanded.
· New Chapter 15, Moderation, discusses the analysis of interaction in multiple regression, including how to generate line graphs to describe the nature of interactions between quantitative predictors.
· New Chapter 16, Mediation, provides a thorough and updated discussion of tests for hypotheses about mediated causal models. This chapter includes complete instructions how to do mediation analysis if you do not have access to a structural equation modeling program, and an optional brief introduction to the AMOS© structural equation modeling program, available as an SPSS add-on, as another way to test mediated models.
Because two new chapters were added in the middle of the book, all chapters from Chapter 15 to end of the book have been renumbered in the second edition.
· Chapter 21 (Chapter 19 in the first edition) has a new section on the different ways that SPSS handles missing scores when forming summated scales using the SPSS Mean and Sum functions.