Update slides

Author: Robinlovelace

slides/road-safety.qmd

@@ -15,18 +15,28 @@ Reproducible data science for road safety research
 
 ## Agenda
 
--   **13:00-14:00** Networking lunch
--   **14:00-14:15** Introduction to reproducible research
--   **14:15-14:30** New datasets and tools (Richard Owen, Agilysis)
--   **14:30-16:00** Workshop
--   **16:00 onwards** Networking and walk to RS5C reception
+- **13:00-14:00** Networking lunch
+- **14:00-14:15** Introduction to reproducible research
+- **14:15-14:30** New datasets and tools (Richard Owen, Agilysis)
+- **14:30-16:00** Workshop
+- **16:00 onwards** Networking and walk to RS5C reception
 
 ## Prerequisites
 
--   A GitHub account
--   Basic familiarity with R/RStudio
--   A laptop with R, RStudio, and Docker installed
--   A willingness to learn and share!
+### To run the code
+
+- Computer to run the code
+  - Either: A laptop with R, RStudio or VS Code and Docker or similar installed to run the code locally
+  - Or: Access to a cloud-based environment for data science (e.g., GitHub Codespaces or Posit Cloud)
+
+### Learn and share
+
+- An interest in road safety and knowledge of road traffic casualty datasets
+- A willingness to learn and share!
+- A GitHub account (to ask questions on the Discussions page and share your own code)
+- Familiarity with data science tools, e.g. R, Python, RStudio, VS Code
+
+
 
 
 ## Housekeeping
@@ -82,39 +92,39 @@ ggplot() +
 
 ## Workshop Tasks
 
--   Importing collision, casualty and vehicle tables (20 min)
--   Temporal visualisation and aggregation (20 min)
--   Spatial visualisation and aggregation (30 min)
--   Joining STATS19 tables (20 min)
+- Importing collision, casualty and vehicle tables (20 min)
+- Temporal visualisation and aggregation (20 min)
+- Spatial visualisation and aggregation (30 min)
+- Joining STATS19 tables (20 min)
 
 ## Task 1: Importing tables (20 min)
 
--   Learn how to load the main STATS19 tables (collision, casualty, vehicle) using the `stats19` R package.
--   Explore the structure and key variables in each table.
+- Learn how to load the main STATS19 tables (collision, casualty, vehicle) using the `stats19` R package.
+- Explore the structure and key variables in each table.
 
 See [Chapter 4](https://itsleeds.github.io/rrsrr/04-pkgs.html) and [Chapter 8](https://itsleeds.github.io/rrsrr/08-join.html) for details.
 
 ## Task 2: Temporal visualisation (20 min)
 
--   Aggregate collision data by time (e.g., by month or day of week).
--   Create time series plots to identify trends and patterns.
+- Aggregate collision data by time (e.g., by month or day of week).
+- Create time series plots to identify trends and patterns.
 
 See [Chapter 6 on temporal data](https://itsleeds.github.io/rrsrr/06-time.html).
 
 ## Task 3: Spatial visualisation (30 min)
 
--   Convert collision data to spatial format and plot on a map.
--   Aggregate collisions by area (e.g., by local authority).
--   Create maps to visualise spatial patterns.
+- Convert collision data to spatial format and plot on a map.
+- Aggregate collisions by area (e.g., by local authority).
+- Create maps to visualise spatial patterns.
 
 See [Chapter 7 on spatial data](https://itsleeds.github.io/rrsrr/07-space.html).
 
 ![](https://itsleeds.github.io/rrsrr/figures/road-casualties.png)
 
 ## Task 4: Joining tables (20 min)
 
--   Join collision, casualty, and vehicle tables to enrich your analysis.
--   Explore relationships between different aspects of road traffic incidents.
+- Join collision, casualty, and vehicle tables to enrich your analysis.
+- Explore relationships between different aspects of road traffic incidents.
 
 See [Chapter 8 on joining tables](https://itsleeds.github.io/rrsrr/08-join.html).
 
@@ -131,5 +141,5 @@ For fast finishers or anyone wanting to go the extra mile:
 
 ## Thank you!
 
--   **Questions?** Get in touch via email or [GitHub Discussions](https://github.com/itsleeds/tds/discussions).
+- **Questions?** Get in touch via email or [GitHub Discussions](https://github.com/itsleeds/tds/discussions).
 -