storytelling with data: #43 misleading graphs
An episode of the storytelling with data podcast podcast, hosted by storytelling with data, titled "storytelling with data: #43 misleading graphs" was published on May 6, 2021 and runs 54 minutes.
May 6, 2021 ·54m · storytelling with data podcast
Summary
A good data visualization can reveal and communicate insights. But bad graphs abound. In this episode, Cole chats with Ben Jones about misleading graphs. They discuss a number of common issues, including missorted time, miscalculated area, going against expected norms, spurious correlations, and more. Tune in for tips on how to read graphs and spot issues and avoid being duped, as well as strategies to consider when graphing data so the visualizations you create don’t inadvertently misinform. LINKS: Ben Jones | @dataremixed | Data Literacy Books by Ben mentioned: Learning to See Data, Avoiding Data Pitfalls Ben’s repository of graphical gaffes: What NOT to Do Book: Mind in Motion (Barbara Tversky) Book: Graphic Methods for Presenting Facts (Williard C. Brinton) Article: Linear vs. Quadratic Change (Robert Kosara) Article: Why not to use two axes, and what to do instead (Lisa Charlotte Rost) Article: The public do not understand logarithmic graphs used to portray COVID-19 Site: ourworldindata.org Site: spurious correlations Site/books: Calling Bullshit (Carl Bergstrom & Jevin West) Tweet/graph: Who emits the most? (Greta Thunberg) Resource: Ben’s “16 chart reading tips” checklist SWD workshops: see upcoming dates & register (use discount code PODCAST10 at checkout)
Episode Description
A good data visualization can reveal and communicate insights. But bad graphs abound. In this episode, Cole chats with Ben Jones about misleading graphs. They discuss a number of common issues, including missorted time, miscalculated area, going against expected norms, spurious correlations, and more. Tune in for tips on how to read graphs and spot issues and avoid being duped, as well as strategies to consider when graphing data so the visualizations you create don’t inadvertently misinform.
LINKS:
Ben Jones | @dataremixed | Data Literacy
Books by Ben mentioned: Learning to See Data, Avoiding Data Pitfalls
Ben’s repository of graphical gaffes: What NOT to Do
Book: Mind in Motion (Barbara Tversky)
Book: Graphic Methods for Presenting Facts (Williard C. Brinton)
Article: Linear vs. Quadratic Change (Robert Kosara)
Article: Why not to use two axes, and what to do instead (Lisa Charlotte Rost)
Article: The public do not understand logarithmic graphs used to portray COVID-19
Site: ourworldindata.org
Site: spurious correlations
Site/books: Calling Bullshit (Carl Bergstrom & Jevin West)
Tweet/graph: Who emits the most? (Greta Thunberg)
Resource: Ben’s “16 chart reading tips” checklist
SWD workshops: see upcoming dates & register (use discount code PODCAST10 at checkout)
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