A Case for Bayesian Statistics in Critical Quantitative Research in Education

Over the last two decades, two frameworks have emerged that combine critical theories with quantitative methodology. These frameworks are QuantCrit – a quantitative instantiation of Critical Race Theory – and CritQuant, a more recent framework grown out of Quantitative Criticalism. Both frameworks offer ways in which quantitative scholars can strengthen the criticality of their research by incorporating critical theories such as Critical Race Theory into their research questions, design, data, analysis, and interpretation. Yet, as long as these frameworks continue to use traditional quantitative approaches to analysis, neither escapes the philosophical, methodological, or historical challenges that plague the traditional framework. This paper argues that adopting a Bayesian statistical framework, as opposed to traditional (frequentist) framework, may assuage some of these challenges. To the extent that Bayesian statistics address these challenges, it is suggested that a Bayesian approach may be helpful for critical quantitative research in education.