Bayesian statistics have recently become computationally possible for more complex public health research questions. Bayesian method offer a novel approach to public health research, they account for non-normally distributed variables, and provide a probabilistic approach to testing null hypotheses. In this worked example, we compare sexual violence victimization (SV) rates on two- and four-year campuses and test whether contextual alcohol-related factors impact risk of victimization. We chose campus SV and heavy episodic drinking (HED) for this example due to the global public health significance; SV is endemic on college campuses and HED is a robust risk factor of victimization. We hypothesized that 1) students at four-year campuses experience more SV than their two-year campus peers, 2) HED predicts victimization across both campus types, and 3) students who engage in HED experience the same amount of SV risk, regardless of campus type. We found reliable differences in SV and HED across two- and four-year campuses: four-year campus students were twice as likely to have experienced SV (OR=1.98, 90% CI=1.61-2.46) and 2.5 times as likely to engage in HED (OR=2.63 90 CI=2.24-3.10) compared with two-year campus students. Finally, the results suggest campus type does not impact the association between SV and HED; therefore, students who drink heavily experience similar SV risk regardless of the campus type they attend. In addition to understanding how institution type and heavy drinking affect students SV experiences, this study presents a novel statistical approach to violence research and elucidates the experiences of violence for an understudied group of college students (i.e., those who attend a two-year campus). This example highlights how Bayesian approaches are valuable in public health. A Bayesian perspective provides a quantitative approach to establishing similarity across groups, which is of clear value to public health evaluations.