By Paul R. Pace
The NASW Press book “Linear Regression Analysis: Assumptions and Application” provides students with a straightforward introduction to a commonly used statistical model that is appropriate for making sense of data with multiple continuous dependent variables.
Using a relatively simple approach that has been proven through several years of classroom use, the text helps students with little mathematical background to understand and apply the most commonly used quantitative regression model in a wide variety of research settings. Instructors will find that its well-written and engaging style, numerous examples, and chapter exercises will provide essential material that will complement classroom work.
The book is written by two Brigham Young University educators: John P. Hoffmann, PhD, professor in the Department of Sociology; and Kevin Shafer, PhD, assistant professor of social work.
The text may be used as a self-teaching guide by researchers who require general guidance or specific advice regarding regression models; by policymakers who are tasked with interpreting and applying research findings that are derived from regression models; and by those who need a quick reference or a handy guide to linear regression analysis.
Social work and other social and behavioral science students and researchers need to have a suite of research tools to conduct studies. Regression analysis is a popular tool that is used in numerous studies to examine statistical relationships among variables. Yet there are few books that offer straightforward and easy-to-follow instruction regarding this type of analysis.
Most books rely too much on mathematical and symbolic representations of regression analysis, even though many students do not have a sufficient background in mathematics and are often put off by the high level of sophistication required to master these techniques.
NASW Press products are available in eBook and print at NASWPress.org.