In this manuscript, we discuss the substantial importance of Bayesian reasoning in Social Science research. Particularly, we focus on foundational elements to fit models under the Bayesian paradigm. We aim to offer a frame of reference for a broad audience, not necessarily with specialized knowledge in Bayesian statistics, yet having interest in incorporating this kind of methods in studying social phenomena. We illustrate Bayesian methods through case studies regarding political surveys, population dynamics, and standardized educational testing. Specifically, we provide technical details on specific topics such as conjugate and non-conjugate modeling, hierarchical modeling, Bayesian computation, goodness of fit, and model testing.

翻译：本文中，我们探讨了贝叶斯推理在社会科学研究中的重要意义。特别地，本文聚焦于在贝叶斯框架下拟合模型的基础要素。我们旨在为广泛的受众（不一定是具备贝叶斯统计学专业知识的读者，但对将此类方法应用于社会现象研究感兴趣者）提供参考框架。通过政治调查、人口动态和标准化教育测试等案例研究，我们阐述了贝叶斯方法的具体应用。具体而言，我们提供了共轭与非共轭建模、分层建模、贝叶斯计算、拟合优度以及模型检验等特定主题的技术细节。