Confident Spatial Analysis and Statistics in R & GeoDa - Online
Date:
16/07/2024 - 17/07/2024
Organised by:
NCRM, University of Southampton
Presenter:
Dr Nick Bearman
Level:
Advanced (specialised prior knowledge)
Contact:
Jacqui Thorp
Training and Capacity Building Coordinator, National Centre for Research Methods, University of Southampton
Email: jmh6@soton.ac.uk
Venue: Online
Description:
In this online course, run over two mornings, we will show you how to prepare and conduct spatial analysis on a variety of spatial data in R, including a range of spatial overlays and data processing techniques. We will also cover how to use GeoDa to perform exploratory spatial data analysis, including making use of linked displays and measures of spatial autocorrelation and clustering.
The course covers:
- Understanding and being able to interpret Spatial Autocorrelation measure Moran's I
- Understanding Local Indicators of Spatial Association statistic
- Perform Spatial Decision Making in R
- Perform Point in Polygon analysis using different approaches
- Be aware of the advantages and disadvantages of using point based or polygon based data
- Using buffers as a part of spatial decision making
By the end of the course participants will:
- Be aware of some spatial statistics concepts and be able to apply them to their own data using GeoDa
- Be able to perform spatial decision making
- Understand the limitations and benefits of working with data in this way
This course is aimed as PhD students, post-docs and lecturers who have some existing knowledge of using R as a GIS and want to develop their knowledge of spatial stats and spatial decision making in R. Some prior knowledge of both R and GIS is required. It is also appropriate for those in public sector and industry who wish to gain similar skills.
Students will be using R, RStudio and GeoDa.
Students need to have completed my Introduction to Spatial Data and Using R as a GIS (https://www.ncrm.ac.uk/training/show.php?article=13142) course, or have equivalent experience. This includes:
Using R to import, manage and process spatial data
Design and creation of choropleth maps
Use of scripts in R
Working with loops in R to create multiple maps
For more information, please look at the link above or contact X.
Students will need R (v > 4.0), and the sf, tmap, dplyr libraries. They will also need RStudio (v > 2023.01 or greater)
No prior knowledge of GeoDa is needed. It can be downloaded following the instructions at https://nickbearman.github.io/installing-software/geoda. Version 1.20 or greater is required.
THIS COURSE WILL RUN OVER TWO MORNINGS (10AM TO 1PM) AND EQUATES TO ONE TEACHING DAY FOR PAYMENT PURPOSES.
Cost:
The fee per teaching day is: • £30 per day for registered students • £60 per day for staff at academic institutions, Research Councils researchers, public sector staff, staff at registered charity organisations and recognised research institutions. • £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.
Website and registration:
Region:
South East
Keywords:
Quantitative Data Handling and Data Analysis, Spatial Data Analysis, Geographical Information System (GIS), Spatial data, Spatial statistics, Geospatial
Related publications and presentations:
Quantitative Data Handling and Data Analysis
Spatial Data Analysis
Geographical Information System (GIS)