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 JAGS. An introduction to 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 JAGS.
3. Generalised linear models with applications to real data using 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 2020/21, 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%
||Written feedback will be provided on the coursework assignments. Students will also receive oral feedback about their progress during the workshops and office hours.
|No Exam Information
On completion of this course, the student will be able to:
- Solve practical statistical modelling problems using JAGS.
- Choose and apply appropriate Bayesian statistical models and interpret the results.
- Prepare written reports based on Bayesian statistical analysis.
|Bayesian Data Analysis (3rd edition). Gelman, Carlin, Stern, Dunson, Vehtari and Rubin. CRC Press |
Core statistics. Wood, Simon N. Cambridge University Press, 2015.
|Graduate Attributes and Skills
|Course organiser||Dr Daniel Paulin
|Course secretary||Miss Gemma Aitchison
Tel: (0131 6)50 9268