2024/25 Taught Postgraduate Module Catalogue

GEOG5007M Geodemographics and Neighbourhood Analysis

15 creditsClass Size: 40

Module manager: Paul Norman
Email: p.d.norman@leeds.ac.uk

Taught: 1 Feb to 31 May (4mth)(adv yr), 1 Mar to 31 May View Timetable

Year running 2024/25

Pre-requisite qualifications

Students should normally have completed the PGCert year of the programme before attempting this module, or be able to evidence equivalent prior learning through other educational programmes or work experience.

This module is mutually exclusive with

GEOG5255M

Geodemographics and Neighbourhood Analysis

This module is not approved as an Elective

Module summary

Area characteristics about neighbourhoods have widespread use in analyses which inform policy decision making in public (local and national government), and private (commercial) organisations as well as the third sector (charities). Area characteristics are also linked to individual level data to determine variations in health and educational application, for example.On this module, students will learn how to construct a variety of area measures and methods to incorporate these in analyses. The knowledge and skills involved are highly useful in many career settings including academic, public, private and third sector settings.

Objectives

This module equips students to analyse and use area (neighbourhood) characteristics to underpin decision making (local planning, policy evaluation, marketing etc). A range of measures are introduced and applied at the small-area level (urban/health research), urban-rural classifications (environmental, planning and social science applications) and geodemographics (business and marketing). Students will consider:

1. Sources of census, admin and commercial data for measuring area characteristics
2. How to devise small-area indicators (from a theoretical and applied perspective)
3. How to use these indicators in a variety of applications
The module is taught using hands-on practical activities and accompanying reading and private study.

Learning outcomes
On successful completion of the module students will have demonstrated the following learning outcomes relevant to the subject:
1. Identify and critique appropriate census, administrative, survey and commercial data sources for measuring area characteristics.
2. Apply data reduction techniques to generate indicators of area type and appreciate their applications.
3. Construct, test, evaluate and apply geodemographic classifications at the area level, and relate these to lifestyles and purchasing behaviours.
4. Appreciate ethical and confidentiality constraints when working with individual and small-area data; conceptual issues of scale including MAUP and ecological fallacy.

Skills Learning Outcomes

On successful completion of the module students will have demonstrated the following skills learning outcomes:
5. Digital Skills’ for ‘Critical Evaluation’ achieved through cleaning, processing and preparing data suitable for and during analysis
6. ‘Problem solving & analytical skills’ for presenting and explaining socio-economic data in an appropriate format
7. ‘Technical Skills’ in selecting and carrying out suitable data reduction methods relative to a problem or task
8. ‘Work Ready Skills’ through the ability to utilise data-driven findings to propose solutions and/or recommendations in response to a problem/task

Syllabus

Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module.

Teaching methods

Delivery type	Number	Length hours	Student hours
Discussion forum	8	8.00	16.00
Individual Support	8	1.00	8.00
Independent online learning hours			48.00
Private study hours			78.00
Total Contact hours			24.00
Total hours (100hr per 10 credits)			150.00

Private study

Private study and online learning includes directed and independent wider reading, independent practical work and researching/undertaking module assessments and related tasks.

Opportunities for Formative Feedback

Formative feedback will be provided during practical activities where students will be encouraged to post outputs to devoted unit-by-unit discussion boards. This will allow for peer critique in addition to staff comments. Note that the outputs requested here will differ from those required as part of the summative assessments.

The module leader will also be on hand to provide support (email / Teams / discussion board / etc) during the teaching weeks, in advance of assessment. Whilst not directly formative assessment, this will ensure that the students receive feedback / support on matters of need.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Coursework	30.00
Assignment	Coursework	70.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 29/04/2024 16:14:37

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