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  6. BI5505: Introduction to Bayesian Inference

BI5505: INTRODUCTION TO BAYESIAN INFERENCE (2015-2016)

Last modified: 25 Mar 2016 11:38


Course Overview

This course is one of the few postgraduate courses in Europe to provide an introduction to Bayesian inference, which is increasingly used in advanced quantitative research. A combination of lectures and personal research will provide you with the core concepts necessary to understand recent research in your field and apply Bayesian approaches to your own research. Hands-on computer tutorials will also allow you to implement statistical models in a Bayesian context and provide you with the essential skills for taking it further.

Course Details

Study Type Postgraduate Level 5
Term Second Term Credit Points 7.5 credits (3.75 ECTS credits)
Campus None. Sustained Study No
Co-ordinators
  • Dr Thomas Cornulier
  • Dr Alex Douglas
  • Professor David Lusseau

Qualification Prerequisites

None.

What courses & programmes must have been taken before this course?

  • One of MRes Ecology & Environmental Sustainability (Studied) or MRes Applied Marine and Fisheries Ecology (Studied) or MSc Ecology & Environmental Sustainability (Studied) or MSc Applied Marine and Fisheries Ecology (Studied) or MSci Biological Sciences (Studied)
  • Either Any Postgraduate Programme (Studied) or BI4015 Grant Proposal (Passed)
  • Either Any Postgraduate Programme (Studied) or MSci Biological Sciences (Studied)
  • Either Any Postgraduate Programme (Studied) or BI5009 Experimental Design and Analysis (Studied)
  • Either Any Postgraduate Programme (Studied) or BI5010 Statistics for Complex Study Designs (Studied)

What other courses must be taken with this course?

None.

What courses cannot be taken with this course?

None.

Are there a limited number of places available?

No

Course Description

Week 1: Introduction to Bayesian statistics. After a refresher in probability theory and linear modelling, students are introduced to Bayes theorem, Bayesian inference, and estimation tools. Week 2-3: Bayesian implementaion of models for various study designs. Students will learn to implement statistical models in the R/BUGS language and fit them to ecological data. Students will gain experience in the visualisation and validation of models and focus on their ecological interpretation. Students will start by implementing relatively simple models that they have already covered using a frequentist approach in previous statistics courses (BI5009 and BI5010) and progress to models suited to more advanced study designs.

Associated Costs

None

Contact Teaching Time

Information on contact teaching time is available from the course guide.

Teaching Breakdown

More Information about Week Numbers


Details, including assessments, may be subject to change until 30 August 2024 for 1st term courses and 20 December 2024 for 2nd term courses.

Summative Assessments

1 online assessment via myaberdeen and 1 marked practical.

Formative Assessment

There are no assessments for this course.

Feedback

None.

Course Learning Outcomes

None.
 

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