论文标题
本科统计课程中的贝叶斯计算
Bayesian Computing in the Undergraduate Statistics Curriculum
论文作者
论文摘要
自1990年代的计算发展以来，贝叶斯统计数字已取得了巨大的动力。逐渐地，贝叶斯方法论和软件的进步使应用统计学家更容易获得贝叶斯技术，并且反过来又可能在本科生中改变了贝叶斯教育。本文提供了有关实施贝叶斯计算方法的各种选项的概述，该方法动机了，以实现特定的学习成果。每种计算方法的优点和缺点是根据作者在课堂上使用这些方法的经验来描述的。目的是为在本科统计课程中引入贝叶斯方法的讲师提供有关计算选择的指导。
Bayesian statistics has gained great momentum since the computational developments of the 1990s. Gradually, advances in Bayesian methodology and software have made Bayesian techniques much more accessible to applied statisticians and, in turn, have potentially transformed Bayesian education at the undergraduate level. This article provides an overview on the various options for implementing Bayesian computational methods motivated to achieve particular learning outcomes. The advantages and disadvantages of each computational method are described based on the authors' experience in using these methods in the classroom. The goal is to present guidance on the choice of computation for the instructors who are introducing Bayesian methods in their undergraduate statistics curriculum.
