You left out the most recent famous example, the Lancet chart of heat deaths vs cold deaths with the x axis distorted by truncating most of the cold side but leaving the end labeled the same as the hot side with a broken squiggly line.
If the majority of us are watching short-form videos and looking at infographics or charts for 1.5 seconds per piece, I wonder about the nature of being fooled, getting it or being entertained in the process.
Apparent engagement online isn’t real engagement in that context. That’s one reason I like Substack where blogging isn’t dead and you can go deeper into a topic if you want to.
Ramaswamy states, "The number of climate-disaster-related deaths is down by 98% over the last century."
Apart from whatever number he is using and whatever his source, the population of the world is four times higher today than a century ago. If the incidence of "climate-disaster-related deaths" was 2% then and 2% now, by the raw numbers, that's a 75% decline.
There's a good book called Proofiness about manipulators' distortion of data gathering, analysis, display, and interpretation.
I learned the power of pretty graphs in my first job, as an engineering intern in a major aerospace company. I was running simulations on a mainframe, and graphing the results on this new computer called a Macintosh. The graphs were so pretty that the managers never questioned them. They could have been my biorhythms.
Really helpful tips. I certainly took away several questions I'll be asking myself when interpreting internet graphs.
It reminds me of a class offered by my alma mater where a couple of professors try to educate students on this very topic, aptly titled "Calling Bullshit." The syllabus and lectures are publicly available, and they even have a book out. https://callingbullshit.org/index.html
Also, he just produces an impressive amount of high-quality short-form econ video content, so could be worth checking out for any big econ bloggers thinking about trying out that medium *wink wink nudge nudge*
Good article... but you left off one of the most famous misleading (though aptly named) graphs - the "Laugher (sic) Curve". Totally ridiculous... Keep 'em coming, Noah!
I note that there seem to be more left-coded than right-coded graphs here. Is this because left-wing political messaging is more likely to go viral; because progressives are more inclined to use data to back up their arguments (albeit not always correctly); because progressives really are less statistically aware; or all or none of the above?
How not to be fooled by viral charts
You left out the most recent famous example, the Lancet chart of heat deaths vs cold deaths with the x axis distorted by truncating most of the cold side but leaving the end labeled the same as the hot side with a broken squiggly line.
https://www.thelancet.com/cms/attachment/82137275-383a-4b3d-aad5-e4b8e9f132a9/gr3.jpg
If the majority of us are watching short-form videos and looking at infographics or charts for 1.5 seconds per piece, I wonder about the nature of being fooled, getting it or being entertained in the process.
Apparent engagement online isn’t real engagement in that context. That’s one reason I like Substack where blogging isn’t dead and you can go deeper into a topic if you want to.
How about this one, from Vivek Ramswamy interviewed by Andrea Mitchell on MSNBC (not a chart, but still...):
https://www.google.com/search?client=safari&rls=en&q=Andrea+Mitchell%27s+interview+of+Vivek+Ramaswamy&ie=UTF-8&oe=UTF-8#fpstate=ive&vld=cid:4a9723eb,vid:uEs0H1NG-DM,st:0
Ramaswamy states, "The number of climate-disaster-related deaths is down by 98% over the last century."
Apart from whatever number he is using and whatever his source, the population of the world is four times higher today than a century ago. If the incidence of "climate-disaster-related deaths" was 2% then and 2% now, by the raw numbers, that's a 75% decline.
Completely off topic, but this is the funniest bunny video I have ever seen. Obviously, none of us appreciates tomatoes enough.
https://twitter.com/RabbitEveryHour/status/1701098242572775536?utm_campaign=wp_todays_worldview&utm_medium=email&utm_source=newsletter&wpisrc=nl_todayworld&s=20
When do we get the dump of other charts that have pissed you off?
There's a good book called Proofiness about manipulators' distortion of data gathering, analysis, display, and interpretation.
I learned the power of pretty graphs in my first job, as an engineering intern in a major aerospace company. I was running simulations on a mainframe, and graphing the results on this new computer called a Macintosh. The graphs were so pretty that the managers never questioned them. They could have been my biorhythms.
I used to have a whole tumblr of bad visualisations. Then they started getting so numerous that I stopped maintaining/ “collecting” them
https://www.tumblr.com/badvisualisations
Nice article. I was also inspired by Summers chart. But in this case to write a fully fledged defense of it https://open.substack.com/pub/shakoist/p/larry-summers-chart-is-fine?r=jhraj&utm_medium=ios&utm_campaign=post
Absolutely fantastic 🔥
Really helpful tips. I certainly took away several questions I'll be asking myself when interpreting internet graphs.
It reminds me of a class offered by my alma mater where a couple of professors try to educate students on this very topic, aptly titled "Calling Bullshit." The syllabus and lectures are publicly available, and they even have a book out. https://callingbullshit.org/index.html
Thanks, this was a fun (and hopefully useful) read!
I'd recommend Christopher Clarke's video on the first graph as a sharable for anyone with family members who are addicted to short-form video content:
https://www.tiktok.com/@econchrisclarke/video/7277754625564871979
Also, he just produces an impressive amount of high-quality short-form econ video content, so could be worth checking out for any big econ bloggers thinking about trying out that medium *wink wink nudge nudge*
Good article... but you left off one of the most famous misleading (though aptly named) graphs - the "Laugher (sic) Curve". Totally ridiculous... Keep 'em coming, Noah!
Great text, thanks.
I note that there seem to be more left-coded than right-coded graphs here. Is this because left-wing political messaging is more likely to go viral; because progressives are more inclined to use data to back up their arguments (albeit not always correctly); because progressives really are less statistically aware; or all or none of the above?
Nice work..thanks
great article!