Dates: Tue 20th Oct and Wed 21st October 2020
Time: 10am – 1pm
Online: (Zoom Details Tbc)
In these two morning sessions, we will discuss the Internet User Classification and Retail Centre Typology datasets from the CDRC and the methods used to create them. K-means clustering is used to create many different data sets, including the geodemographic classification, OAC. We will discuss the IUC and RCT datasets, how and why they were created, and what they can be used for. We will also discuss and show you how to use the K-means clustering method to create your own classification, using IUC as an example.
The training will consist of the 2 x 3 hour sessions which will run over Zoom. These will consist of a small section of presentations, some seminar style discussions and 1-to-1 supported practical work. There will also be a short video you will be required to watch before the course. We will work with R and RStudio.
If you have not used R before, or would like a refresher, a short R as a GIS course will be available for you to complete in your own time before the course. We may ask participants to complete a short quiz to confirm the required skill level in R, and to then complete the refresher course before attending the session if needed.
After the course participants will:
- Understand what the Internet User Classification and Retail Centre Typology dataset are, and what they can and cannot be used for
- Understand how K-means clustering is used to create a classification
- Be able to apply the K-means clustering method to their own data
- Have example code to create a K-means clustering classification in R
Pricing and discounts
Pricing is on the event tab but there is a 20% discount for SLA members bringing it down to £56.00.
Students only pay £30.
*If your employment has been affected as a result of COVID-19 and you wish to partake in this training please email KE.Coordinator@sbs.ox.ac.uk to discuss your options.
*Please note: Courtesy of the ESRC grant the pricing for this event has been subsidised.
For further details contact – email@example.com
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