Introduction to Bayesian methods with an emphasis on data analysis. Topics include prior choice, posterior assessment, hierarchical modelling and model fitting using R, JAGS and other freely available software.
|Paper title||Bayesian Data Analysis|
|Teaching period||Second Semester|
|Domestic Tuition Fees (NZD)||$904.05|
|International Tuition Fees (NZD)||$3,954.75|
- STAT 260 and (STAT 270 or 261)
- Schedule C
- Arts and Music, Science
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- Teaching staff
To be advised
To be determined
- Graduate Attributes Emphasised
- Global perspective, Interdisciplinary perspective, Lifelong learning, Scholarship,
Communication, Critical thinking, Environmental literacy, Information literacy, Research,
View more information about Otago's graduate attributes.
- Learning Outcomes
On successful completion of the paper, students will be able to:
- Understand the difference between Bayesian and frequentist statistics.
- Fit and interpret basic statistical models using Bayesian inference.
- Use modern software for Bayesian data analysis.
- Understand the role of prior distributions.
- Assess the fit of Bayesian models.