The course will introduce the basic concepts and methods in Bayesian statistics, including specifying the prior distribution, deriving the posterior distribution and conducting statistical inference base on the posterior. This course will also focus on the statistical computing problems in Bayesian analysis, and teach the students to use R to perform Bayesian sampling and inference. The aim of this course is to provide the students who have already got the knowledge of frequentist’s statistics with the core philosophy and fundamental methods in Bayesian statistics, and help them lay a solid foundation for further exploration in this area.