Module Search

MATH4071: Topics in Statistics IV

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type	Open
Level	4
Credits	20
Availability	Not available in 2024/2025
Module Cap
Location	Durham
Department	Mathematical Sciences

Prerequisites

Statistical Methods III (MATH 3051).

Corequisites

None.

Excluded Combinations of Modules

Topics in Statistics III (MATH 3361).

Aims

To provide a working knowledge of the theory, computation andpractice of a number of specialised statistical tools, complementingStatistical Methods III.

Content

Likelihood-based inference
Generalised linear models
Log-linear modelling of contingency tables
Advanced topic: one of multivariate analysis, time seriesanalysis, medical statistics.
Reading material in an advanced area of statistics chosenby the lecturer.

Learning Outcomes

Subject-specific Knowledge:

By the end of the module students will:
be aware of a wide range of applicable statisticalmethodology.
have a systematic and coherent understanding of the theory,computation and application of the mathematics underlying thestatistical topics studied.
have acquired a coherent body of applicable knowledge onlikelihood methods as a general approach to inference.
have acquired a coherent body og knowledge of generalisedlinear methods and log-linear modelling.
have a knowledge and understanding of a substantial topic inan advanced area of statistics obtained by independent study.

Subject-specific Skills:

In addition students will have specialised mathematicalskills in the following areas which can be used with minimal guidance:Modelling, Computation.

Key Skills:

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Lectures demonstrate what is required to be learned and theapplication of the theory to practical examples.
Computer practicals consolidate the studied material andenhance practical understanding.
Assignments for self-study develop problem-solving skills andenable students to test and develop their knowledge andunderstanding.
Formatively assessed assignments provide practice in theapplication of logic and high level of rigour as well as feedback forthe students and the lecturer on students' progress.
The end-of-year examination assesses the knowledge acquiredand the ability to solve predictable and unpredictableproblems.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total
Lectures	40	2 per week for 20 weeks (omitting two slots) and 2 in term 3	1 Hour	40
Computer Practicals	2	In unused lecture slots in first two terms	1 Hour	2
Problems Classes	8	Four in each of terms 1 and 2	1 Hour	8
Preparation and Reading				150
Total				200

Summative Assessment

Component: Examination		Component Weighting: 100%
Element	Length / Duration	Element Weighting	Resit Opportunity
Written examination	3 hours	100

Formative Assessment

More information

If you have a question about Durham's modular degree programmes, please visit our FAQ webpages, Help page or our glossary of terms. If you have a question about modular programmes that is not covered by the FAQ, or a query about the on-line Undergraduate Module Handbook, please contact us.

Prospective Students: If you have a query about a specific module or degree programme, please Ask Us.

Current Students: Please contact your department.