Bayesian Statistics
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课程详情
课程评价
spContent=Bayesian Analysis is a course for students of statistics and related majors. In addition to the fundamental theory of Bayesian inference, examples and case studies will be given in each Chapter with detailed programming code in R, WinBUGS/OpenBUGS, JAGS and related R packages, such as R2OpengBUGS, BRugs, rjags, R2jags, runjags and nimble. After learning the lectures in the course, the students are required to get a good command of common Bayesian model formulation and Bayesian computation methods for Bayesian data analysis.
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课程概述

Bayesian statistics is a subject for applied data analysis. With profound philosophy behind it provides new ideas about learning from all sources of information which is not possible in frequentist statistics.It has been widely used in nearly all the areas related to data, including economics, econometrics, marketing, social science, medical reserch, education, ecology, weather forcasting, and date science, etc. It can tackle nearly all kinds of data, big, small or even missing. The key point of the subject is to do Baysian inference by combine current sample information and prior information with some special techniques or algorithms. Students can be trained to have deep insight to look different kinds of data, to have stronger ability of programming in R, and comprehensive knowledge of statistics. This course will be focused on the idea of Bayesian learning, basic principle of main algorithms and case studies accompnied with R or packages related to easy-to-understand BUGS languages. All the code ane availale in Rmarkdown which is reproducible on the student side. 

授课目标

The purpose of this course is to cultivate students' ability to use Bayesian analysis method to analyze data. After finishing the the course, students should be able to 

  1. Master the basic concepts, basic theories and calculation methods in Bayesian statistical analysis;  
  2. Learn Bayesian modeling and analysis methods for specific data;
  3. Master the professional words and expressions of Bayesian statistical analysis, and understand some simple references; 
  4. Learn to carry out Bayesian statistical analysis through R programming and BUGS related R software package.
课程大纲
预备知识
  1. Basic statistics
  2. R programming
  3. Intermediate level calculus
参考资料
  1. M. K. Cowles, Applied Bayesian Statistics: with R and OpenBUGS Examples, Springer, 2013.
  2. Jim Albert, Bayesian Computation with R (2nd Edtion), Springer, 2009
  3. J. K. Kruschke, Doing Bayesian Data Analysis: A Tutorial with R and BUGS, Academic Press/Elsvier, 2011.
  4. Chi Yau, R Tutorial with Bayesian Statistics Using OpenBUGS (Kindle Edition)
  5. R in Action: Data Analysis and Graphics with R, Manning Publications, 2011.