Postgraduate Course: Bayesian Data Analysis (MATH11175)
Course Outline
| 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 |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| 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. |
| Course description |
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)
| Pre-requisites |
Students MUST have passed:
Bayesian Theory (MATH11177)
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
|
| Academic year 2020/21, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 12,
Seminar/Tutorial Hours 10,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
76 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 100%, Examination 0% |
| Feedback |
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 |
Learning Outcomes
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.
|
Reading List
Bayesian Data Analysis (3rd edition). Gelman, Carlin, Stern, Dunson, Vehtari and Rubin. CRC Press
Core statistics. Wood, Simon N. Cambridge University Press, 2015.
|
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | BDAn,bayesian,data analysis,statistics |
Contacts
| Course organiser | Dr Daniel Paulin
Tel:
Email: dpaulin@ed.ac.uk |
Course secretary | Miss Gemma Aitchison
Tel: (0131 6)50 9268
Email: Gemma.Aitchison@ed.ac.uk |
|
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