Bayesian Analysis Made Easy
Bayesian methods have become popular as a useful tool for data analysis and decision making. Modern software has made this possible and the methods are now applied in a wide range of scientific application areas from medicine to ecology.
This course is aimed at those who are new to Bayesian statistics and want to develop an understanding and application of the methods. Emphasis will be on practical data analysis and interpretation. Only essential theory will be outlined.
The RJAGS package, a widely used specialist software for Bayesian analysis, will be used in the presentations as well as other software as appropriate.
The course will include an introduction to and practical exercises in RJAGS. The R software will also be used as a graphical tool. In addition, participants will be able to use SAS and Stata during the hands-on computer sessions.
Who Should Attend?
Scientists and related who want an introduction to Bayesian methods for data analysis. No prior knowledge of Bayesian statistics is required. A working knowledge of linear and generalised linear models and statistical distributions is required. No previous experience of RJAGS is required.
How You Will Benefit
By the end of the course, you will have a firm understanding of Bayesian methods and their flexibility. You will also have acquired a working knowledge of specialised software for Bayesian data analysis and will be able to fit and interpret linear and generalised linear models.
What Do We Cover?
Choice of Software
Practical work may be done in: R, SAS, Stata
Note: For practical work, participants must bring their own laptop with a fully licensed version of their chosen software.
The practical exercises use mostly R; in addition, SAS and Stata may also be used for fitting Bayesian models.