2014/15 Taught Postgraduate Module Catalogue

GEOG5520M Quantitative and Spatial Methods

15 creditsClass Size: 45

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

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2014/15

This module is mutually exclusive with

GEOG5891M

Spatial Analysis and GIS (WUN)

Module replaces

GEOG5660M Quantitative Research Methods (option)GEOG5070M Spatial Analysis (option)

This module is approved as an Elective

This module is approved as a Skills Elective

Module summary

This module explains and demonstrates geography relevant quantitative and spatial analysis methods.Through both lectures and computer practical sessions, students gain experience in the application of geographical analysis methods to real world problems and learn to use appropriate statistical and GIS software.

Objectives

In the context of geography relevant quantitative and spatial analysis methods the module seeks to:
1) demonstrate and explain appropriate quantitative approaches to solving geographical/spatial problems using data;
2) give students practical experience in the application of geographical analysis methods;
3) give students a detailed and critical understanding of the theoretical and practical problems involved in quantitative and spatial analysis;
4) give students an understanding of the approaches taken to solve geographical problems in academic and industry situations;
5) enable students to learn and use appropriate statistical and GIS software.

Skills outcomes
Knowledge of data types and their relationships to geographical entities.

Familiarity with traditional statistical models including skills in carrying out correlation and multiple regression of geographically referenced data using statistical software (currently SPSS).

Skills in carrying out spatial analyses using GIS and other application specific software (mainly ArcGIS).

Skills in the interpretation and display of model outputs.

Syllabus

• Spatial Analysis, GIS functionality and software
• Spatial data and descriptive statistics
• Spatial statistics. Regression and correlation
• Probabilities and their use in statistical and mathematical models
• Point pattern analysis and spatial cluster hunting
• Interpolation and data estimation
• Area classification and data reduction
• Boundaries and related geographical issues including MAUP and ecological fallacy

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	11	1.50	16.50
Practical	11	2.00	22.00
Seminar	1	1.00	1.00
Tutorial	2	1.00	2.00
Private study hours			108.50
Total Contact hours			41.50
Total hours (100hr per 10 credits)			150.00

Private study

Students will undertake directed reading of advised texts; both books and academic papers. They will practice the software skills demonstrated in lectures and learned in the supported practicals.

Opportunities for Formative Feedback

The practical sessions will enable academic and PG colleagues to see first hand how well students are learning the software and whether they are noting the appropriate outputs needed for interpretation.

Outside contact hours, students can check their practical work against model answers and also use MCQs (formative assessment) posted on the VLE to check their understanding/progress.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	2,000 words	50.00
Report	2,000 words	50.00
Total percentage (Assessment Coursework)		100.00

The coursework will involve two projects which report on: Assignment 1: An analysis explaining the geographical distribution of an outcome based on area data (inherently a statistical analysis) Assignment 2: A cluster analysis of point data and a classification of area data (inherently a spatial analysis) Both require links with the literature on the subject and/or on methods used and entail quantitative analysis with statistical outputs reported and mapped where appropriate.

Reading list

The reading list is available from the Library website

Last updated: 06/01/2015

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