Don't Get Fooled! Avoid The Illusion of Causality in Charts

Hosted by Enrico Bertini

Mon, Jun 16, 2025

4:00 PM UTC (1 hour)

Virtual (Zoom)

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53 students

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Rhetorical Data Visualization for Data Professionals
Enrico Bertini
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What you'll learn

Spot charts with false cause-and-effect claims

You'll learn how to identify charts that suggest (explicitly or implicitly) cause and effect where there may be none.

Identify different types of causality in charts

You'll learn how different chart types and combinations of data types lead to different types of illusory causality.

Scientific background on causality in charts

You'll learn about scientific studies that show how people derive causality from charts.

Why this topic matters

We often work with data to make decisions and to convince others that a given intervention will have a desired effect. Cause and effect are everything in decision-making. But charts do not always tell the truth. The truth comes from your ability to reason effectively about cause and effect.

You'll learn from

Enrico Bertini

University professor, researcher, and educator with 15+ years of experience.

Dr. Enrico Bertini has been teaching and conducting research in Data Visualization for over 15 years. He holds a PhD in Computer Engineering from the University of Rome, La Sapienza. He has been a faculty member at New York University for almost 10 years and, since 2022, has been a faculty member at Northeastern University, holding an appointment in the intersection of Computer Science and Art+Design. Dr. Bertini is the founder and co-host of Data Stories, a popular data podcast that was active from 2012 to 2022. He also writes a data newsletter called FILWD with a community of 2600+ subscribers.

Learn directly from Enrico Bertini

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