Statistical Inference (L.6) (G5216)

15 credits, Level 6

Spring teaching

Part 0: Revision of Probability

a. Random Variables and probability distributions

b. Revision of some well-known probability distributions

c. Expectation and interpretation of moments

d. Conditional Probability and Bayes’ rule

e. Conditional Expectation and properties

Part 1: Frequentist Statistics

a. Likelihood and Sufficiency

b. Point estimators

c. Hypothesis Testing

d. Interval estimators (confidence intervals and their connection with hypothesis tests)

Part 2: Bayesian Statistics

a. The Bayesian Paradigm

b. Bayesian Models

c. Prior Distributions

Part 3: Model Selection

a. Frequentist Model Selection

b. Bayesian Model selection and Bayes Factors

Throughout this module, numerous practical real-world examples will be discussed during practical sessions and analysed using the R programming language.


85%: Lecture
15%: Practical


20%: Coursework (Portfolio, Problem set, Software exercise)
80%: Examination (Computer-based examination)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 33 hours of contact time and about 117 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.


This module is offered on the following courses: