Applying Bayesian Statistics using Stan (in-person)
Ben Lambert
All DPhil students Research staff Statistics
Wednesday, 31 January 2024, 9.30am to 5pm
This course aims to provide solid foundations to implementing linear regression, three types of Generalised Linear Models, and hierarchical models.
COURSE DETAILS
Stan is a powerful tool for performing inference for systems encountered in the sciences and social sciences and, importantly, it has an active user/developer community which can help you when you get stuck.
In this session, we will introduce users to Stan and show how to perform inference for a variety of models, including discrete parameter models, hierarchical models and differential equations.
LEARNING OUTCOMES
By the end of the session participants will be able to:
• Develop a basic understanding of the open-source ‘Stan’ probabilistic programming language.
• Apply Bayesian inference to research problems, including their own.
INTENDED FOR
All
Additional Information
COURSE PRE-REQUISITE
Ideally, some basic knowledge of Bayesian statistics obtained, for example, through the introduction course.
Also, some knowledge of a mathematical programming language, for example: R, Matlab, Python, Mathematica, or C++.
PARTICIPANTS WILL NEED TO BRING LAPTOPS.
NUMBER OF PLACES
30
COURSE LEADER
Ben Lambert
TIME / Date
09.30 - 17.00 | 31st January 2024
BOOKING INFORMATION
Book your place on Applying Bayesian Statistics using Stan by clicking here.
TERMS & CONDITIONS
When registering for this course, please check our Terms and Conditions.