When and how to communicate quality and uncertainty
Abstract
This session will focus on best practices for communicating uncertainty, data quality issues, and limitations of analyses through language and visual storytelling, to explore how these complex issue can be represented in ways that are both accurate and engaging.
By the end of the session, participants will understand why it’s important to be upfront about data quality issues and uncertainty and be aware of best practice principles they can use to know when and how to discuss it. There will be a focus on communicating with stakeholders, particularly those with a non-technical background, to enable them make better evidence-based decisions with confidence in the data underlying them.
Attendees will learn about approaches to communicating data and statistical quality without overwhelming or misleading audiences. They will also develop techniques for visualising uncertainty, using a variety of different chart types.
By the end of this session, participants will:
- Understand how communicating quality issues and uncertainty can increase trustworthiness and know when it is important and appropriate to talk about
- Have an understanding of the language used to describe and communicate quality, especially for non-technical audiences
- Know when it is and isn’t appropriate to show uncertainty in visualisations, and which chart types are most effective at doing so
More information can be found on the event website. Organised jointly by the RSS Edinburgh Local Group, the RSS AI Task Force and the RSS Medical Section.