Sampling bias is rarely obvious, and that’s exactly why it matters.

In this short 10-minute session, we’ll explore how limitations in data collection and sampling choices can shape the story an audience takes away, even when the analysis and visualisation are technically correct.

Using real-world examples, I’ll show how certain populations can be unintentionally over-represented, under-represented, or excluded entirely, and how visual design decisions can either mask these gaps or make them transparent.

This session focuses on awareness rather than accusation, understanding the limits of what a sample can tell us, and making those limits clearer through thoughtful data communication and visual design.