Academic Item Menu


This course presents General interference theory based on maximum likelihood and on Bayes methods is reviewed. Estimation, confidence set construction and hypothesis testing are discussed within decision-theoretic framework. Computationally intensive methods such as bootstrap are discussed and are compared to asymptotic approximations such as saddlepoint and empirical likelihood.Pre-requisites: 24 units of level III mathematics or a degree in a numerate discipline or permission of the Head of Department.Note: Course not offered every year - contact the School for more information.
Study Level


Offering Terms

Term 1



Delivery Mode

Fully on-site

Indicative contact hours


Course Outline

To access course outline, please visit:


Pre-2019 Handbook Editions

Access past handbook editions (2018 and prior)

Helpful utilities like sharing or printing this page
Share Link via Email
Download PDF