| Unit name | Theory of Inference |
|---|---|
| Unit code | MATH35600 |
| Credit points | 20 |
| Level of study | H/6 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Professor. Wood |
| Open unit status | Not open |
| Pre-requisites |
MATH11300 Probability 1 and MATH11400 Statistics 1 (or MATH10013 Probability and Statistics). |
| Co-requisites |
None |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Unit Aims
Statistical inference is about drawing quantitative conclusions about things that we are interested in from data that we can collect. This unit provides an overview of the theory and methods used to do this, comparing the Bayesian and the frequentist approaches, with a practical focus on using the theory in practice.
Unit Description
The course covers statistical model, statistical methods of uncertainty quantification, statistical model comparison, model checking, the difference between inference about causality and association, and the practical implementation of Bayesian and maximum likelihood based approaches.
Relation to Other Units
This units builds on Statistics 1, and uses technical material covered in first year mathematics courses. It complements the more specialized courses in Generalized linear modelling, Bayesian statistics and Statistics 2 (none of which are required as prerequisites).
To gain an understanding of some key principles of statistical inference, and how these impact upon current practice across a range of fields.
Transferable Skills: This unit exemplifies the general skills of other mathematical units, of logical thinking and the concept of proof, problem solving, abstraction, a facility with notation, self-study and self-appraisal. Some examples and homeworks will use the statistical computing environment R.
Lectures, problems classes, homeworks to be done by students, Office Hours.
80% written examination
20% coursework
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
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