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Factor analysis is perhaps one of the most widely used statistical procedures in the social sciences. An examination of the PsycINFO database for the period between January 1, 2000, and September 19, 2018, revealed a total of approximately 55,000 published journal articles indexed with the keyword factor analysis. Similar results can be found by examining the ERIC database for education research and JSTOR for other social sciences. Thus, it is not an exaggeration to state that understanding factor analysis is key to understanding much published research in the fields of psychology, education, sociology, political science, anthropology, and the health sciences. The purpose of this book is to provide you with a solid foundation in exploratory factor analysis, which, along with confirmatory factor analysis, represents one of the two major strands within this broad field. Indeed, a portion of this first chapter will be devoted to comparing and contrasting these two ways of conceptualizing factor analysis. However, before getting to that point, we first need to describe what, exactly, factors are and the differences between latent and observed variables. We will then turn our attention to the importance of having strong theory to underpin the successful use of factor analysis, and how this theory should serve as the basis upon which we understand the latent variables that this method is designed to describe. We will then conclude the chapter with a brief discussion of the software available for conducting factor analysis and an outline of the book itself. My hope in writing this book is to provide you, the reader, with a sufficient level of background in the area of exploratory factor analysis so that you can conduct analyses of your own, delve more deeply into topics that might interest you, and confidently read research that has used factor analysis. If this book achieves these goals, then I will count it as a success.