Schedule, syllabus and examination date

Course content

Confidence distributions are posterior distributions obtained without priors. In contrast to Bayesian posteriors they are unbiased distributions for parameters. Statistical inference with confidence distributions synthesises Bayesian and frequentist inference, which are in conflict.

This course gives a general introduction to the construction and uses of confidence distributions in different settings, from simple parametric models to more complicated situations. Confidence distributions are useful for applied inference and reporting. It provides a platform for effectively combining information across different information sources (meta-analysis). Statistical inference with confidence distributions, and also other non-Bayesian distributional inference, is in rapid development.

Learning outcome

The course gives the background and tools for constructing, interpreting and using confidence distributions in a wide spectrum of models and situations, including problems related to combining information across diverse data sources.

Admission to the course

Students admitted at UiO must?apply for courses?in Studentweb. Students enrolled in other Master's Degree Programmes can, on application, be admitted to the course if this is cleared by their own study programme.

Nordic citizens and applicants residing in the Nordic countries may?apply to take this course as a single course student.

If you are not already enrolled as a student at UiO, please see our information about?admission requirements and procedures for international applicants.

Overlapping courses

Teaching

2 + 1 hours of lectures/exercises per week throughout the semester.