Syphilis is a growing public health concern in Brazil, disproportionately affecting vulnerable populations. Socioeconomic factors, such as education, income, and access to healthcare, significantly influence its incidence. This study compares six statistical methods—Pearson and Spearman correlations, univariate and multivariate linear regression, logarithmic regression, and Poisson regression—to analyze these relationships using data from Minas Gerais, Brazil. The results highlight strong associations between the incidence of syphilis and both educational and health indicators, emphasizing the importance of preventive policies. Methodological comparisons reveal significant discrepancies, with some approaches misestimating the impact of variables due to multicollinearity or data distribution effects. These findings underscore the importance of selecting appropriate statistical models to ensure accurate epidemiological interpretations and support the development of effective public health strategies.