Using Ordinary Least Squares in Higher Education Research: A Primer

Abstract

This chapter serves as a primer in utilizing ordinary least squares (OLS) in higher education research, by providing an overview of this commonly used quantitative approach, which often includes simple linear regression models and multiple linear regression models. The first section of the chapter reviews current literature to explain ways that OLS allows researchers to identify the goals of OLS and differentiate them from basic descriptive analyses and bivariate analyses. It then discusses the types of research questions that may be answered by OLS. The second section walks readers through an example application of OLS using a real-world dataset, reviewing the definitions, key components, and analytic steps in using OLS. The following section addresses important considerations in testing statistical assumptions and the influence of assumption violation before applying OLS. The fourth section further discusses the significance of considering heterogeneous effects in contemporary higher education. The chapter closes with topics related to interpreting findings, as well as the broader application of OLS in higher education research contexts.