# 贝叶斯统计简介11.11

A Brief Introduction to Bayesian Statistics

Point estimation and hypothesis testing about parameters are the major subjects in classical statistics, and the parameter is thought to be an unknown, but fixed, quantity. Classical statistics is directed towards the use of the sample information in making inference about the parameter, without regard to the nonsample information, such as the prior information about the parameter, and possible consequences of the reference. Bayesian inference utilize prior information formally. And Bayesian decision theory introduces also the loss function into the statistical field, with the loss function one can connect the reference with the economical loss, so that the Bayesian theory can more easily apply to the economic fields.

The main contents of the course are as follows: prior distribution and posterior distribution, the determination of the prior distribution, Bayesian inference, utility function and loss function, Bayesian decision. The students can learn the basic Bayesian theory and its application from this course.

Probability and statistics are required for this course.