The complexity of social problems necessitates that social work researchers utilize multivariate statistical methods in their investigations. Having a thorough understanding of basic statistics can facilitate this process as multivariate methods have as their foundation many of these basic statistical procedures. In this pocket guide, the authors introduce readers to three of the more frequently used multivariate statistical methods in social work research—multiplelinear regression analysis,analysis of variance and covariance, and path analysis—with an emphasis on the basic statistics as important features of these methods. The primary intention is to help prepare entry level doctoral students and early career social work researchers in the use of multivariate statistical methods by offering a straightforward and easy to understand explanation of these methods and the basic statistics that inform them. The pocket guide begins with a review of basic statistics, hypothesis testing with inferential statistics, and bivariate analytic methods. Subsequent sections describe bivarate and multiple linear regression analyses, one-way and two-way analysis of variance (ANOVA) and covariance (ANCOVA), and path analysis. In each chapter, the authors introduce the various basic statistical procedures by providing definitions, formulas, descriptions of the underlying logic and assumptions of each procedure, and examples of how they have been applied in the social work research literature. The authors also explain estimation procedures and how to interpret results. Each chapter provides brief step-by-step instructions for conducting these statistical tests in Statistical Package for the Social Sciences (SPSS) and AMOS (SPSS, Inc. 2011), based on data from the National Educational Longitudinal Study of 1988 (NELS: 88). Finally, the book offers a companion website that provides more detailed instructions, as well as data sets and worked examples.