The Bayesian Way: Uncertainty, Learning, and Statistical Reasoning
贝叶斯之道:不确定性、学习与统计推理
This paper offers a comprehensive introduction to Bayesian inference, combining historical context, theoretical foundations, and core analytical examples. Beginning with Bayes' theorem and the philosophical distinctions between Bayesian and frequentist approaches, we develop the inferential framework for estimation, interval construction, hypothesis testing, and prediction. Through canonical models, we illustrate how prior information and observed data are formally…