Understanding Misleading Graphs

Introduction

• Exaggerated claims in advertising and politics are common.
• Graphs are often seen as objective, but they can also be misleading.

Common Misleading Techniques using Graphs

Distorting the Scale

• Example: 1992 Chevy ad claimed their trucks were more reliable than Toyota's.
  • Chevy: 98% trucks still on the road
  • Toyota: 96.5% trucks still on the road
  • Misleading factor: Y-axis scale was between 95-100%, exaggerating the difference.
  • Proper scale (0-100%) shows negligible difference.
• Bar Graphs: Misleading when the difference in bar sizes appears disproportionate to actual values.

Manipulating the X-axis

• Example: Graph showing U.S. unemployment rise (2008-2010).
  • Scale is inconsistent; 15-month span compressed compared to 6 months prior.
  • Consistent data points show job losses tapering off by 2009.
  • Omitted context: Starts post-major financial collapse (Great Depression).

Cherry Picking Data

• Choosing specific time ranges or data points to exclude significant events.
• Omitting data can obscure important trends.

Misleading by Omitting Context

• Example: Super Bowl viewership chart.
  • Appears popularity is increasing.
  • Missing context: Population growth, stable ratings.

Importance of Context in Graph Interpretation

• Example: Ocean temperature data from 1880 to 2016.
  • First graph: Average annual temperature looks insignificant.
  • Second graph: Yearly temperature variation highlights ecological impact.

Conclusion

• Graphs should be used to clarify data.
• Visual software increases graph usage but also potential for misuse.
• When viewing graphs:
  • Examine labels, numbers, scale, and context.
  • Consider the narrative being presented.