Module 6: Spatial Data Analysis Prerequisites
Sun 11 Oct, Sun 18 Oct, ... Sun 29 Nov 2020
Description
Introducing students to methods of data analysis that are relevant to spatial data. Discussing nature of Geographic Information Science (GISc), describing how space is conceptualised and represented in a GIS.
Target audience
Mphil Students from participating departments taking the Social Science Research Methods Course as part of their research degree
Prerequisites
A basic course in statistics up to and including statistical inference (hypothesis testing: confidence intervals), and the regression model.
Sessions
Number of sessions: 8
| # | Date | Time | Venue | Trainer |
|---|---|---|---|---|
| 1 | Sun 11 Oct 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 2 | Sun 18 Oct 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 3 | Sun 25 Oct 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 4 | Sun 1 Nov 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 5 | Sun 8 Nov 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 6 | Sun 15 Nov 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 7 | Sun 22 Nov 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
| 8 | Sun 29 Nov 2020 14:00 - 16:00 | 14:00 - 16:00 | Geography Dept | Prof. R.P. Haining |
Topics covered
- Session 1: GIScience and the nature of geographical space
- Session 2: Properties of spatial data
- Session 3: Quantifying spatial structure
- Session 4: Spatial data quality
- Session 5: Spatial interpolation:geometric and distance weighting methods
- Session 6: Exploratory spatial data analysis
- Session 7: Cluster detection
- Session 8: Regression analysis applied to spatial data
Objectives
- The objective is to introduce students to the methods of data analysis that are relevant for spatial data.
Aims
- understand how data quality is assessed
- attend practical classes on
- quantifying spatial structure - testing for spatial auto-correlation
Format
- Lectures held in the Small Lecture Theatre, Geography Department, Downing Site
- Practicals held in the Top Lab, Geography Department, Downing Site
Taught using
GIS software
Assessement
Satisfactory completion of 5 practicals.
Textbook(s)
Haining, R.P. (2003) Spatial Data Analysis: Theory and Practice. P.432. CUP.
Notes
- To gain the maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking. Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.
Duration
Eight sessions of two hours
Frequency
Eight times in Michaelmas term
Theme
Advanced Statistics
Booking / availability