《贝叶斯分析》课程教学大纲 一、课程基本信息 课程代码：18100152 课程名称：贝叶斯分析 英文名称：Bayesian Statistics 课程类别：专业课 时：32 学分：2 适用对象：统计学等专业大三学生 考核方式：考试 先修课程：微积分、概率论与数理统计 二、课程简介 贝叶斯学派是数理统计中一个重要的学派。它有鲜明的特点和独到的处理方法 在国际上贝叶斯学派与非贝叶斯学派的争论是很多的。本课程重点介绍贝叶斯统计推 断的理论、方法及其基本观点，同时对贝叶斯方法和经典方法在历史上的重大分歧也 适当予以介绍。通过该门课程的学习，使学生能了解贝叶斯学派的基本观点和基本思 想，了解贝叶斯学派和频率学派联系和区别，能够基本地掌握贝叶斯统计的基本理论、 方法，更重要的是了解贝叶斯统计具有特色的一些处理方法以及相应的理论框架，用 以分析问题、解决问题。主要内容有先验分布与后验分布的基本概念、后验分布的计 算方法、估计与假设检验等。 Bayesian school is an important school in mathematical statistics.It has distinctive features and unique treatment methods.There are many disputes between Bayesian and non-Bayesian schools in the world.This course focuses on the theories,methods and basic viewpoints of Bayesian statistical inference.At the same time,the major historical differences between Bayesian and classical methods are also appropriately introduced. Through the study of thiscours,students can understand the basic views and basic ideas of Bayesian school,understand the relationship and difference between Bayesian school and frequency school,and be able to master the basic theories and methods of Bayesian statistics.It is to understand some of the unique processing methods of Bayesian statistics and the corresponding theoretical framework to analyze and solve problems.The main content includes the basic concepts of prior distribution and posterior distribution,the calculation method of posterior distribution,estimation and hypothesis testing,etc 三、课程性质与教学目的1 《贝叶斯分析》课程教学大纲 一、课程基本信息 课程代码：18100152 课程名称：贝叶斯分析 英文名称：Bayesian Statistics 课程类别：专业课 学 时：32 学 分：2 适用对象: 统计学等专业大三学生 考核方式：考试 先修课程：微积分、概率论与数理统计 二、课程简介 贝叶斯学派是数理统计中一个重要的学派。它有鲜明的特点和独到的处理方法， 在国际上贝叶斯学派与非贝叶斯学派的争论是很多的。本课程重点介绍贝叶斯统计推 断的理论、方法及其基本观点，同时对贝叶斯方法和经典方法在历史上的重大分歧也 适当予以介绍。通过该门课程的学习，使学生能了解贝叶斯学派的基本观点和基本思 想，了解贝叶斯学派和频率学派联系和区别，能够基本地掌握贝叶斯统计的基本理论、 方法，更重要的是了解贝叶斯统计具有特色的一些处理方法以及相应的理论框架，用 以分析问题、解决问题。主要内容有先验分布与后验分布的基本概念、后验分布的计 算方法、估计与假设检验等。 Bayesian school is an important school in mathematical statistics. It has distinctive features and unique treatment methods. There are many disputes between Bayesian and non-Bayesian schools in the world. This course focuses on the theories, methods and basic viewpoints of Bayesian statistical inference. At the same time, the major historical differences between Bayesian and classical methods are also appropriately introduced. Through the study of this course, students can understand the basic views and basic ideas of Bayesian school, understand the relationship and difference between Bayesian school and frequency school, and be able to master the basic theories and methods of Bayesian statistics. It is to understand some of the unique processing methods of Bayesian statistics and the corresponding theoretical framework to analyze and solve problems. The main content includes the basic concepts of prior distribution and posterior distribution, the calculation method of posterior distribution, estimation and hypothesis testing, etc. 三、课程性质与教学目的