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Overview

Topics change year to year.

About this paper

Paper title Special Topic
Subject Statistics
EFTS 0.1667
Points 20 points
Teaching period Not offered in 2025 (On campus)
Domestic Tuition Fees ( NZD ) $1,571.48
International Tuition Fees Tuition Fees for international students are elsewhere on this website.
Contact

martin.hazelton@otago.ac.nz    

Teaching staff

Dr Peter Dillingham

Textbooks

No textbook required.

Graduate Attributes Emphasised
Interdisciplinary perspective, Lifelong learning, Scholarship, Communication, Critical thinking, Ethics, Information literacy, Research, Self-motivation.
View more information about Otago's graduate attributes.
Learning Outcomes

On successful completion of the paper students will be able to:

  1. Explain key concepts in Bayesian statistics such as the link between the likelihood, prior and posterior distributions
  2. Understand the relationship between Bayesian and frequentist approaches
  3. Understand sufficient theory to find analytical solutions to standard problems (note: ‘standard’ problems in Bayesian statistics require advanced statistical knowledge)
  4. Be able to independently use R with JAGS or stan to complete Bayesian statistical analyses, including the ability to correctly format and manipulate input different data types, run analyses and diagnostics, and interpret and plot results
  5. Be able to implement their own Markov chain Monte Carlo samplers in R
  6. Communicate results to others and understand the ethical and scientific importance of reproducible research
  7. Independently develop advanced hierarchical statistical models linked to a scientific study, create and perform an appropriate Bayesian analysis

Timetable

Not offered in 2025

Location
Dunedin
Teaching method
This paper is taught On Campus
Learning management system
Blackboard
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