Postgraduate Course: Bayesian Data Analysis (MATH11175)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||The course will provide the students with practical experience of applying Bayesian analyses to a range of statistical models. The statistical analyses will be conducted using the widely used computer package BUGS/JAGS. An introduction to BUGS/JAGS will be provided with additional hands-on experience. Assessment will be by written reports of Bayesian data analyses.
1. Basic principles of applied Bayesian analyses.
2. Introduction to BUGS/JAGS.
3. Generalised linear models with applications to real data using BUGS/JAGS.
4. Mixed effects models.
Entry Requirements (not applicable to Visiting Students)
|| Students MUST have passed:
Bayesian Theory (MATH11177)
||Other requirements|| None
Course Delivery Information
|Academic year 2016/17, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 12,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 100%, Examination 0%
|No Exam Information
On completion of this course, the student will be able to:
- Demonstrate knowledge and practical experience of BUGS/JAGS.
- Ability to choose and apply appropriate Bayesian statistical models and interpret the results.
- Ability to prepare reports on Bayesian statistical analyses.
|Bayesian Data Analysis (3rd edition). Gelman, Carlin, Stern, Dunson, Vehtari and Rubin. CRC Press |
The BUGS Book: A Practical Introduction to Bayesian Analysis. Lunn, Jackson, Best, Thomas and Spiegelhalter. CRC Press
|Graduate Attributes and Skills
|Course organiser||Dr Natalia Bochkina
Tel: 0131 650 8597
|Course secretary||Mrs Frances Reid
Tel: (0131 6)50 4883
© Copyright 2016 The University of Edinburgh - 3 February 2017 4:44 am