Making Sense of Multivariate Data Analysis: An Intuitive Approach

Making Sense of Multivariate Data Analysis is a short introduction to multivariate data analysis (MDA) for students and practitioners in the behavioral and social sciences. It provides a conceptual overview of the foundations of MDA and of a range of specific techniques including multiple regression, logistic regression, discriminant analysis, multivariate analysis of variance, factor analysis, and log-linear analysis. As a conceptual introduction, the book assumes no prior statistical knowledge, and contains very few symbols or equations. Its primary objective is to expose the conceptual unity of MDA techniques both in their foundations and in the common analytic strategies that lie at the heart of all of the techniques. Although introductory, the book encourages the reader to reflect critically on the general strengths and limitations of MDA techniques. Each chapter includes references for further reading accessible to the beginner.

This is an ideal text for advanced undergraduate and graduate courses across the social sciences. Practitioners who need to refresh their knowledge of MDA will also find this an invaluable resource.

John Spicer was an Associate Professor and Head of Psychology at Massey University, New Zealand until the end of 2002, when he took early retirement to devote all of his time to writing books. Earlier, he was a Research Fellow for several years at the University of Auckland, New Zealand, and held Visiting Fellowships at the Universities of Michigan and London. His primary research interests have been in health psychology, and he has published articles mainly on cardiovascular disease and theoretical issues in a variety of international journals. He was coeditor of Social Dimensions of Health and Disease: New Zealand Perspectives (1994). Most of his undergraduate and graduate teaching has focused on research methods, particularly multivariate data analysis. In 2002 he coauthored a chapter on sociological and psychological methods in the fourth edition of the Oxford Textbook of Public Health.